7 Data Engineering jobs in Pakistan
Senior Manager, Data Engineering - Business Intelligence
Posted 3 days ago
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JOB DESCRIPTION
We are seeking a passionate and experienced Senior Manager of Business Intelligence & Data Engineering to lead and develop a high-performing team of engineers. The scope of this role will be broad and multi-tiered, covering all aspects of the Business Intelligence (BI) ecosystem - designing, building, and maintaining robust data pipelines, enabling advanced analytics, and delivering actionable insights through BI and data visualization tools.
You will play a critical role in fostering a collaborative and innovative team environment, while driving continuous improvement across all aspects of the engineering process. Also - key to the success of this role will be an assertiveness and willingness to engage directly with stakeholders, developing relationships while acquiring deep understanding of functional domains (business processes, etc.).
KEY RESPONSIBILITIES
- Lead the design and development of scalable, high-performance data architectures on AWS, leveraging services such as S3, EMR, Glue, Redshift, Lambda, and Kinesis. Architect and manage Data Lakes for handling structured, semi-structured, and unstructured data.
- Manage Snowflake for cloud data warehousing, ensuring seamless data integration, optimization of queries, and advanced analytics. Implement Apache Iceberg in Data Lakes for managing large-scale datasets with ACID compliance, schema evolution, and versioning.
- Drive Data Modeling and Productization: Design and implement data models (e.g., star/snowflake schemas) to support analytical use cases, productizing datasets for business consumption and downstream analytics.
- Work with business stakeholders to create actionable insights using enterprise BI platforms (MicroStrategy, Tableau, Power BI, etc.). Build data models and dashboards that drive key business decisions, ensuring that data is easily accessible and interpretable.
- Ensure that data pipelines, architectures, and systems are thoroughly documented and follow coding and design best practices. Promote knowledge-sharing across the team to maintain high standards for quality and scalability.
- Call upon breadth of experience spanning many technologies and platforms to help shape architectural direction.
- Assist end-users in optimizing their analytic usage, visualizing data in a more efficient and actionable fashion, beyond data dumps and grid reports.
- Promote ongoing adoption of business intelligence content through an emphasis on user experience, iterative design refinement and regular training.
- Implement Observability and Error Handling: Build frameworks for operational monitoring, error handling, and data quality assurance to ensure high reliability and accountability across the data ecosystem.
- Stay Ahead of Industry Trends: Keep abreast of the latest techniques, methods, and technologies in data engineering and BI, ensuring the team adopts cutting-edge tools and practices to maintain a competitive edge.
QUALIFICATIONS
- 10+ years of experience in Data Engineering or a related field, with a proven track record of designing, implementing, and maintaining large-scale distributed data systems.
- 5+ years of work experience in BI/data visualization/analytics.
- 5+ years of people management experience with experience managing global teams.
- Track record of solving business challenges through technical solutions. Be able to articulate the context behind projects and their impact.
- Knowledge of CI/CD tools and practices, particularly in data engineering environments.
- Proficiency in cloud-based data warehousing, data modeling, and query optimization.
- Experience with AWS services (e.g., Lambda, Redshift, Athena, Glue, S3) and managing cloud infrastructure.
- Strong experience in Data Lake architectures on AWS, using services like S3, Glue, EMR, and data management platforms like Apache Iceberg.
- Familiarity with containerization tools like Docker and Kubernetes for managing cloud-based services.
- Hands-on experience with Apache Spark (Scala & PySpark) for distributed data processing and real-time analytics.
- Expertise in SQL for querying relational and NoSQL databases, and experience with database design and optimization.
- Proficiency in creating interactive dashboards and reports using drag-and-drop interfaces in enterprise BI platforms, with a focus on user-friendly design for both technical and non-technical stakeholders.
- Experience in microservices-based architectures, messaging, APIs, and distributed systems.
- Familiarity with embedding BI content into applications or websites using APIs (e.g., Power BI Embedded, MicroStrategy’s HyperIntelligence for zero-code embedding, Tableau’s robust APIs).
- Able to work in a collaborative environment to support rapid development and delivery of results.
- Exhibit an understanding of business problems and translate those into creative, innovative and practical solutions that deliver high quality services to the business.
- Strong communication and presentation skills, with experience delivering insights to both technical and executive audiences.
- Willing to wear many hats and be flexible with a varying nature of tasks and responsibilities.
BONUS POINTS
- Understanding of data science and machine learning concepts, with the ability to collaborate with data science teams.
- Knowledge of Infrastructure as Code (IaC) practices, using tools like Terraform to provision and manage cloud infrastructure (e.g., AWS) for data pipelines and BI systems.
- Familiarity with data governance, security, and compliance practices in cloud environments.
- Domain understanding of Apparel, Retail, Manufacturing, Supply Chain or Logistics.
Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.
#J-18808-LjbffrPrincipal Software Engineer - Platforms and Data Engineering
Posted 3 days ago
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Principal Software Engineer
The Platforms organization at Fanatics is at the heart of our company's data-driven decision making, building foundational capabilities that empower our application/data engineers and data scientists to unlock the power of data. We work relentlessly on enhancing the fan experience with exciting projects across a diverse landscape, including:
- Commerce Applications: Architecting and designing D2C and B2B commerce applications with workloads distributed across a multi-cloud topology to engage fans around the world.
- Storage Infrastructure: Building and managing scalable and reliable data storage solutions.
- Streaming Data Processing: Handling real-time data pipelines with high throughput and low latency.
- Data & Workflow Orchestration: Coordinating complex data processing workflows with efficiency and reliability.
- Messaging Infrastructure: Ensuring secure and efficient communication between applications.
- Big Data Processing: Analyzing massive datasets with speed and accuracy.
- Data Warehouse: Providing a centralized and accessible repository for historical data.
- Real Time OLAP Databases: Enabling fast and interactive data analysis for insights on the fly.
- AI & ML Platforms: Building and maintaining a robust platform that supports the development and deployment of impactful ML models to power applications in areas such as recommender systems and inventory intelligence.
The Opportunity
We are seeking a passionate and experienced Principal Engineer to play a key role in shaping the future of our application, cloud, and data platforms at Fanatics. As a technical leader in the organization, you will be responsible for driving technical innovation, leading large initiatives, and mentoring junior engineers. You will have the opportunity to contribute to building scalable solutions that will empower our entire company to make data-driven decisions and operate more effectively.
Responsibilities
- Design and drive the technical roadmap for the evolution of our platforms, ensuring they are scalable, reliable, and meet the evolving needs of the business.
- Lead large initiatives within the broader Fanatics tech org, collaborating effectively with cross-functional teams including engineering, data science, and product management.
- Provide mentorship and guidance to junior engineers, fostering their growth and development within the team.
- Build data platforms that promote standardization, including data pipeline development, platform tooling, data lake formatting, and data democratization.
- Build and maintain the AI/ML infrastructure to support Fanatics' AI/ML needs, with a focus on standardized MLOps practices, accelerating the adoption and deployment of impactful AI/ML applications across the company.
- Champion data and AI governance best practices, establishing and enforcing data processing principles, design patterns, and practices.
- Build strong cross-functional partnerships with teams across the organization, influencing them to adopt best practices and collaborate effectively.
Qualifications
- 13+ years of experience leading the development of modern cloud-based applications and their integration into a common data platform (or data mesh) to enable business intelligence and optimization.
- Deep technical understanding of distributed systems architecture and the integration of operational systems with analytical systems to enable anomaly detection, business process mining, and optimization at scale.
- Strong expertise in the big data ecosystem, including tools like Apache Kafka, Spark, Iceberg, Airflow, AWS S3, data modeling, data warehouses, OLAP databases, etc.
- Proven experience in data processing, orchestration, data engineering, data quality management, and data governance.
- Excellent communication skills, with the ability to collaborate effectively across teams and provide clear and concise technical guidance.
- Experience with AI/ML platforms and a working knowledge of how data scientists leverage data for AI is a strong plus.
Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.
#J-18808-LjbffrSenior Big Data Engineer
Posted 3 days ago
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Job Area: Engineering Group, Engineering Group > Software Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.
Minimum Qualifications:
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
- OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
- OR PhD in Engineering, Information Systems, Computer Science, or related field.
- 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.
Preferred Qualifications:
- 3+ years of experience as a Data Engineer or in a similar role.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Solid working experience with Python, AWS analytical technologies and related resources (Glue, Athena, QuickSight, SageMaker, etc.).
- Experience with Big Data tools , platforms and architecture with solid working experience with SQL.
- Experience working in a very large data warehousing environment, Distributed System.
- Solid understanding on various data exchange formats and complexities.
- Industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets.
- Strong data visualization skills.
- Basic understanding of Machine Learning; Prior experience in ML Engineering a plus.
- Ability to manage on-premises data and make it inter-operate with AWS based pipelines.
- Ability to interface with Wireless Systems/SW engineers and understand the Wireless ML domain; Prior experience in Wireless (5G) domain a plus.
Education:
- Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline.
- Preferred Qualifications: Masters in CS/ECE with a Data Science / ML Specialization.
Principal Duties and Responsibilities:
- Completes assigned coding tasks to specifications on time without significant errors or bugs.
- Adapts to changes and setbacks in order to manage pressure and meet deadlines.
- Collaborates with others inside project team to accomplish project objectives.
- Communicates with project lead to provide status and information about impending obstacles.
- Quickly resolves complex software issues and bugs.
- Gathers, integrates, and interprets information specific to a module or sub-block of code from a variety of sources in order to troubleshoot issues and find solutions.
- Seeks others' opinions and shares own opinions with others about ways in which a problem can be addressed differently.
- Participates in technical conversations with tech leads/managers.
- Anticipates and communicates issues with project team to maintain open communication.
- Makes decisions based on incomplete or changing specifications and obtains adequate resources needed to complete assigned tasks.
- Prioritizes project deadlines and deliverables with minimal supervision.
- Resolves straightforward technical issues and escalates more complex technical issues to an appropriate party (e.g., project lead, colleagues).
- Writes readable code for large features or significant bug fixes to support collaboration with other engineers.
- Determines which work tasks are most important for self and junior engineers, stays focused, and deals with setbacks in a timely manner.
- Unit tests own code to verify the stability and functionality of a feature.
Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies.
If you would like more information about this role, please contact Qualcomm Careers.
#J-18808-LjbffrData Science & Engineering Lead
Posted 10 days ago
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Overview:
We’re looking for a hands-on Data Science & Engineering Lead to lead our data strategy and help scale a lean, high-impact team. This role blends leadership, architecture, and deep technical work - from building predictive models to designing the infrastructure that powers real-time decision-making. You’ll partner closely with cross-functional teams (Product, Business, Finance, Tech) and take full ownership of analytics delivery from raw data to actionable insight.
This is a builder’s role - ideal for someone who wants deep ownership, startup pace, and the chance to grow as we scale.
Responsibilities:
- Define and deliver our data strategy - from core infrastructure to insights delivery
- Build and mentor a team of 2–5 data scientists and engineers
- Design and deploy predictive models, recommendation systems, and performance analytics
- Architect, deploy, and maintain scalable data pipelines and analytics tooling
- Own and scale robust data pipelines and ensure data integrity across business verticals
- Collaborate closely with stakeholders across Product, Business Finance, and Tech teams to integrate data into daily operations and product decisions
- Act as the go-to person for data strategy, experimentation, and insights
- 5–6 years of relevant experience in data science, engineering or analytics,
- At least 1-2 years in a leading or mentoring small teams (leading 2-5 people) within an agile high tech environment
- Strong command of Python or R; strong SQL skills required
- Deep expertise in data analysis, predictive modeling, designing scalable pipelines, and maintaining analytics infrastructure
- Familiarity with modern BI tools (e.g., Looker, Metabase, Power BI, Tableau)
- Experience working cross functionally with business and product teams
- Startup mindset; strong bias for action, autonomy and ownership; able to apply agile principles and own delivery end to end
- Seniority level Mid-Senior level
- Employment type Full-time
- Job function Engineering and Information Technology
- Industries Hospitality, Food and Beverage Services, and Retail
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#J-18808-LjbffrData Science & Engineering Lead
Posted 9 days ago
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This is a builder’s role - ideal for someone who wants deep ownership, startup pace, and the chance to grow as we scale.
Responsibilities:
Define and deliver our data strategy - from core infrastructure to insights delivery Build and mentor a team of 2–5 data scientists and engineers Design and deploy predictive models, recommendation systems, and performance analytics Architect, deploy, and maintain scalable data pipelines and analytics tooling Own and scale robust data pipelines and ensure data integrity across business verticals Collaborate closely with stakeholders across Product, Business Finance, and Tech teams to integrate data into daily operations and product decisions Act as the go-to person for data strategy, experimentation, and insights
Requirements:
5–6 years of relevant experience in data science, engineering or analytics, At least 1-2 years in a leading or mentoring small teams (leading 2-5 people) within an agile high tech environment Strong command of Python or R; strong SQL skills required Deep expertise in data analysis, predictive modeling, designing scalable pipelines, and maintaining analytics infrastructure Familiarity with modern BI tools (e.g., Looker, Metabase, Power BI, Tableau) Experience working cross functionally with business and product teams Startup mindset; strong bias for action, autonomy and ownership; able to apply agile principles and own delivery end to end
Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
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Senior Machine Learning Engineer (Personalization)
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Manager - Manager Finance Tech Data Engineering (Mashreq Global Network Pakistan)
Posted 11 days ago
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Position holder (Manager - Technology) responsibility of managing our Finance systems, including OFSAA (Oracle Financial Services Analytical Applications), Financial Consolidation, and Regulatory Reporting. The Position holder will play a crucial role in designing and maintaining the finance system architecture that supports these business finance function. This role holder will help in maintaining the data models, ETL tools such as Informatica, and most importantly OFSAA data model. The job holder will be responsibility to manage hybrid team (onshore/Offshore) and supporting business stake holder management.
Key Result Areas
- Data Management: Design, develop, and maintain the data infrastructure that supports the Finance systems, ensuring data accuracy, integrity, and availability.
- Data Modeling: Apply data modeling techniques to design efficient and scalable data structures that support the Finance systems' reporting and analysis requirements.
- ETL Development: Utilize ETL tools like Informatica or like extract, transform, and load data from various sources into the Finance systems, ensuring smooth and accurate data flow.
- Finance System Management: Collaborate with Finance stakeholders to understand their data requirements and ensure that the data infrastructure meets their needs for financial consolidation, regulatory reporting, cost allocation, and profitability reporting.
- Project Management: Experience in managing finance technology projects, ensuring timely delivery with adherence to budgets.
- Communication and Stakeholder Management: Strong communication skills to interact with various stakeholders, including senior management, technical teams, and business users.
- Data Mapping: Perform data mapping exercises to align data from diverse sources to the standardized OFSAA data model, ensuring data consistency and accuracy.
- Data Quality and Governance: Implement data quality and governance processes to maintain high data quality standards across the Finance systems.
- Performance Optimization: Identify and implement performance optimization techniques to ensure efficient data processing and reporting within the Finance systems.
- Integration: Collaborate with IT teams and external vendors to integrate new data sources and applications with the Finance systems.
- Regulatory Compliance: Thorough understanding of regulatory reporting requirements and compliance standards in the banking industry.
Operating Environment, Framework and Boundaries, Working Relationships
- Operates within a fast-paced, dynamic technology landscape, ensuring alignment with the bank's strategic objectives and compliance with regulatory requirements.
- Adheres to internal policies, legal regulations, and ethical standards, with clear boundaries for decision-making authority to manage risks effectively and maintain confidentiality.
- Collaborates closely with cross-functional teams, senior management, and external stakeholders to drive technology initiatives and foster a culture of innovation and continuous improvement.
Problem Solving
- Developed and implemented data-driven solutions that increased operational efficiency through automating processes and optimizing data collection methods.
- Collaborated with cross-functional teams to integrate data from multiple sources, resolving discrepancies.
Decision Making Authority & Responsibility
- Managed data governance and quality control decisions, ensuring data accuracy and integrity for all reporting and analytics processes.
- Drove decisions on data collection and methodology, ensuring high-quality data was available for accurate processing and reporting.
Knowledge, Skills and Experience
- Bachelor’s degree in computer science, Information Technology, or a related field.
- Proven experience as a Data Engineer, handling Finance systems like OFSAA, Financial Consolidation, and Regulatory Reporting.
- Expertise in data modeling techniques and ETL tools (e.g., Informatica) to manage data integration and transformation processes.
- Knowledge of banking finance functions, including financial consolidation, cost allocation, and profitability reporting.
- Familiarity with big data technologies and their applications in data management and analysis. Understanding of Hadoop architecture, tools like HDFS, Hive, Sqoop, Spark is critical for the tool.
- Proficiency in SQL and database management systems.
- Analytical mindset with a focus on data accuracy and attention to detail.
- Strong problem-solving skills and the ability to work independently as well as in a team environment.
- Excellent communication and collaboration skills to engage with stakeholders across different teams.
- Seniority level Mid-Senior level
- Employment type Full-time
- Job function Finance and Information Technology
- Industries Banking
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Sign in to set job alerts for “Finance Manager” roles.Karachi Division, Sindh, Pakistan 2 days ago
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Team Leader - Business Banking VRM (Mashreq Global Network Pakistan) Country Treasury Operations Manager (Mashreq Digital Bank Pakistan)Karachi Division, Sindh, Pakistan 3 days ago
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Senior Manager - Financial Reporting & ICFR (Mashreq Digital Bank Pakistan) Financial and Regulatory Reporting Senior AnalystKarachi Division, Sindh, Pakistan 1 year ago
Karachi Division, Sindh, Pakistan 1 month ago
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#J-18808-LjbffrDirector of Software Engineering - Data Governance (AIML)
Posted 2 days ago
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If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you.
As a Director of Software Engineering at JPMorgan Chase within the Chief Data & Analytics Office's Data Governance Engineering team, you will play a pivotal role in supporting the firm in delivering services to clients and advancing the firm-wide agenda for Data & Analytics. You will lead firm-wide initiatives through a unified Data Analytics Platform, in alignment with the firm's Data & AI strategy. Collaborating with engineering teams, you will be responsible for creating designs, establishing best practices, and developing guidelines along with scalable frameworks to effectively manage large volumes of data, ensuring interoperability, compliance with data classification requirements, and maintaining data integrity and accessibility. You will work closely with Product & Engineering teams to promote unified engineering execution across multiple initiatives, strategically designing and building applications that address real-world use cases. Your expertise in software, applications, technical processes, and product management will be essential in promoting complex projects and initiatives, serving as a primary decision-maker and a champion of innovation and solution delivery. As part of the Product Delivery team, you will design and build scalable cloud-native foundational data governance products and services that support the Data Risk Pillars, providing a unified experience through the CDAO platform.
Job responsibilities
- Collaborate with product and engineering teams to deliver robust firm wide data governance solutions that drive enhanced customer experiences.
- Provides critical day-to-day leadership and strategic thinking, working with team of engineers and architects to align cross-functional initiatives, ensuring they are feasible both fiscally and technically.
- Makes decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures.
- Champions the firm’s culture of diversity, equity, inclusion, and respect
- Will be leading the consolidation and convergence effort of the Data Governance capabilities under unified CDAO Platform and other priority firmwide initiatives related to BCBS 239, data lineage, controls & data quality.
- Enable engineering teams to Develop, enhance, and maintain established standards and best practices, Drive, self-service, and deliver on a strategy to operate on a build broad use of Amazon's utility computing web services (e.g., AWS EC2, AWS S3, AWS RDS, AWS CloudFront, CloudWatch, EKS)
- Identify opportunities to improve resiliency, availability, secure, high performing platforms in Public Cloud using JPMC best practices.
- Implement continuous process improvement, including but not limited to policy, procedures, and production monitoring and reduce time to resolve. Identify, coordinate, and implement initiatives/projects and activities that create efficiencies and optimize technical processing.
- Measure and optimize system performance, with an eye toward pushing our capabilities forward, getting ahead of customer needs, and innovating to continually improve.
- Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Graph DB and Open Source RDBMs databases, Container Orchestration services including Kubernetes, and a variety of AWS tools and services.
Required qualifications, capabilities, and skills.
- Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.
- Experience in building or supporting environments on AWS using Terraform, which includes working with services like EKS, ELB, RDS, and S3.
- Strong understanding of business technology drivers and their impact on architecture design, performance, and monitoring best practices.
- Dynamic individual with excellent communication skills, capable of adapting verbiage and style to the audience at hand and delivering critical information in a clear and concise manner.
- Strong experience in managing stakeholders at all levels.
- Strong analytical thinker with business acumen and the ability to assimilate information quickly, with a solution-based focus on incident and problem management.
- Hands-on experience with one or more cloud computing platform providers
- Experience in architecting for private and public cloud environments and in re-engineering and migrating on-premises data solutions to the cloud.
- Proficiency in building on emerging cloud server less managed services to minimize or eliminate physical and virtual server footprints.
- Experience with high-volume, mission-critical applications and their interdependencies with other applications and databases.
- Proven work experience with container platforms such as Kubernetes. Strong understanding of architecture, design, and business processes. Keen understanding of financial and budget management, control, and optimization of public cloud expenses. Experience working in large, collaborative teams to achieve organizational goals. Passionate about building an innovative culture.
Preferred qualifications, capabilities, and skills
- Bachelor’s /Master’s degree in Computer science or other technical, scientific discipline
- Experience implementing multi-cloud architectures anddeep understanding of cloud infrastructure design, architecture, and cloud migration strategies.
- Demonstrated proficiency in technical solutions, implementing firm wide solutions and experience in data governance vendor product knowledge is a plus.
- Certifications in target areas (AWS Cloud/Kubernetes etc.)
- Experience leading Data Governance and Data Risk Reporting platforms is a preferred.
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