48 Big Data Technologies jobs in Pakistan

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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. Call upon breadth of experience spanning many technologies and platforms to help shape architectural direction.
7. Assist end-users in optimizing their analytic usage, visualizing data in a more efficient and actionable fashion, beyond data dumps and grid reports.
8. Promote ongoing adoption of business intelligence content through an emphasis on user experience, iterative design refinement and regular training.
9. 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.
10. 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

1. 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.
2. 5+ years of work experience in BI/data visualization/analytics.
3. 5+ years of people management experience with experience managing global teams.
4. Track record of solving business challenges through technical solutions. Be able to articulate the context behind projects and their impact.
5. Knowledge of CI/CD tools and practices, particularly in data engineering environments.
6. Proficiency in cloud-based data warehousing, data modeling, and query optimization.
7. Experience with AWS services (e.g., Lambda, Redshift, Athena, Glue, S3) and managing cloud infrastructure.
8. Strong experience in Data Lake architectures on AWS, using services like S3, Glue, EMR, and data management platforms like Apache Iceberg.
9. Familiarity with containerization tools like Docker and Kubernetes for managing cloud-based services.
10. Hands-on experience with Apache Spark (Scala & PySpark) for distributed data processing and real-time analytics.
11. Expertise in SQL for querying relational and NoSQL databases, and experience with database design and optimization.
12. 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.
13. Experience in microservices-based architectures, messaging, APIs, and distributed systems.
14. 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).
15. Able to work in a collaborative environment to support rapid development and delivery of results.
16. Exhibit an understanding of business problems and translate those into creative, innovative and practical solutions that deliver high quality services to the business.
17. Strong communication and presentation skills, with experience delivering insights to both technical and executive audiences.
18. Willing to wear many hats and be flexible with a varying nature of tasks and responsibilities.

BONUS POINTS

1. Understanding of data science and machine learning concepts, with the ability to collaborate with data science teams.
2. 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.
3. Familiarity with data governance, security, and compliance practices in cloud environments.
4. 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.

Karachi

Remote

One-year contractual role

We are seeking a talented Data Scientist with strong expertise in SAS Viya and significant experience in
the banking and telecom sectors. In this role, you will leverage advanced analytics and machine learning
techniques to derive actionable insights from large datasets, optimizing business decisions and
strategies. Your knowledge of SAS Viya, along with your domain expertise, will be essential for
developing predictive models, improving customer experience, and enhancing operational efficiency.

Description

• Develop, implement, and fine-tune predictive and statistical models using SAS Viya to address
  business needs, with a focus on customer segmentation, churn prediction, fraud detection, and
  risk management in the banking and telecom sectors.
• Conduct deep data analysis and feature engineering to uncover patterns, trends, and insights
  that drive business strategies in banking and telecom operations.
• Integrate and process large datasets from various sources (e.g., transactional data, customer
  behavior data, financial data) and leverage SAS Viya’s cloud-native capabilities for scalable data
  processing and analysis.
  
• Apply machine learning algorithms and artificial intelligence techniques to develop models that
  enhance customer experience, optimize marketing campaigns, and improve operational
  efficiency.
• Present findings and insights through clear and actionable visualizations and reports using SAS
  Visual Analytics and other reporting tools, making complex data accessible to stakeholders.
• Continuously improve model performance by fine-tuning algorithms and optimizing data
  workflows to handle large volumes of data efficiently.

Requirements

• 5+ years of experience as a Data Scientist with a strong background in SAS Viya and experience
  working in banking and telecom sectors.
• Strong proficiency in SAS Viya (including SAS Visual Analytics, SAS Visual Data Mining and
  Machine Learning, and SAS Cloud Analytics).
• Experience with predictive modeling, statistical analysis, and machine learning algorithms in
  both sectors.
• Excellent communication skills, with the ability to translate technical findings into business
  insights for non-technical stakeholders.

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:

1. Commerce Applications: Architecting and designing D2C and B2B commerce applications with workloads distributed across a multi-cloud topology to engage fans around the world.
2. Storage Infrastructure: Building and managing scalable and reliable data storage solutions.
3. Streaming Data Processing: Handling real-time data pipelines with high throughput and low latency.
4. Data & Workflow Orchestration: Coordinating complex data processing workflows with efficiency and reliability.
5. Messaging Infrastructure: Ensuring secure and efficient communication between applications.
6. Big Data Processing: Analyzing massive datasets with speed and accuracy.
7. Data Warehouse: Providing a centralized and accessible repository for historical data.
8. Real Time OLAP Databases: Enabling fast and interactive data analysis for insights on the fly.
9. 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

1. 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.
2. Lead large initiatives within the broader Fanatics tech org, collaborating effectively with cross-functional teams including engineering, data science, and product management.
3. Provide mentorship and guidance to junior engineers, fostering their growth and development within the team.
4. Build data platforms that promote standardization, including data pipeline development, platform tooling, data lake formatting, and data democratization.
5. 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.
6. Champion data and AI governance best practices, establishing and enforcing data processing principles, design patterns, and practices.
7. Build strong cross-functional partnerships with teams across the organization, influencing them to adopt best practices and collaborate effectively.

Qualifications

1. 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.
2. 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.
3. Strong expertise in the big data ecosystem, including tools like Apache Kafka, Spark, Iceberg, Airflow, AWS S3, data modeling, data warehouses, OLAP databases, etc.
4. Proven experience in data processing, orchestration, data engineering, data quality management, and data governance.
5. Excellent communication skills, with the ability to collaborate effectively across teams and provide clear and concise technical guidance.
6. 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.

SWATX is seeking a highly skilled and experienced Data Science Manager to lead our growing data science team. In this strategic role, you will be responsible for overseeing the development and implementation of data-driven solutions to solve complex business challenges. You will mentor and guide a team of data scientists, driving innovation and excellence in analytics and machine learning. If you are a strong leader with a passion for data science and a proven track record of delivering impactful solutions, we invite you to join us.

1. Lead and mentor a team of data scientists, providing guidance on best practices in data analysis, machine learning, and statistical modeling.
2. Develop and execute the data science strategy aligned with business objectives, ensuring that data-driven insights are integrated into decision-making processes.
3. Oversee the design and implementation of innovative data science projects that drive value for the organization.
4. Collaborate with cross-functional teams to identify opportunities for leveraging data to improve products, services, and operational efficiency.
5. Build and maintain strong relationships with stakeholders, understanding their data needs and ensuring timely delivery of insights.
6. Monitor and evaluate the performance of data science models and adjust strategies as necessary to achieve desired results.
7. Promote a data-driven culture within the organization by communicating the value of data science initiatives to stakeholders at all levels.
8. Stay updated on the latest trends and developments in data science and analytics, and integrate new methodologies and tools as appropriate.

Devsinc is seeking a talented Data Science Engineer who will play a pivotal role in designing, implementing, and optimizing data-driven solutions that enhance our machine learning capabilities. The ideal candidate has a strong background in data engineering combined with machine learning and is passionate about applying modern technologies to drive innovation. You will collaborate with data scientists, analysts, and software engineers to create robust data pipelines and deploy advanced models.

Key Responsibilities:

• Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources.
• Collaborate with data scientists to transform machine learning models into production-ready applications.
• Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process.
• Evaluate and integrate new data management and processing technologies to enhance analytics capabilities.
• Create and manage data repositories, following best practices for data governance and security.
• Develop documentation and provide training to team members on data systems and workflows.
• Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
• Stay updated on the latest industry trends and technologies in data engineering and machine learning.
• Lead the development and deployment of machine learning models that drive key business metrics and outcomes.
• Build and maintain scalable data pipelines and feature stores for training and inference use cases.
• Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery.
• Monitor and retrain models in production to ensure performance over time and handle data drift issues.
• Contribute to architectural decisions on data platforms and model-serving infrastructure.
• Mentor junior team members and help shape best practices in data science engineering.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline.
• 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions.
• Demonstrated experience translating business problems into data science projects with measurable outcomes.
• Prior experience working closely with business stakeholders to operationalize models and drive ROI.

Soft Skills:

• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills, both verbal and written, to convey technical concepts effectively.
• Ability to work collaboratively in a fast-paced team environment and manage multiple priorities.
• Motivated self-starter with a passion for learning and applying new technologies.

Devsinc is seeking a talented Data Science Engineer who will play a pivotal role in designing, implementing, and optimizing data-driven solutions that enhance our machine learning capabilities. The ideal candidate has a strong background in data engineering combined with machine learning and is passionate about applying modern technologies to drive innovation. You will collaborate with data scientists, analysts, and software engineers to create robust data pipelines and deploy advanced models.

Key Responsibilities:

• Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources.
• Collaborate with data scientists to transform machine learning models into production-ready applications.
• Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process.
• Evaluate and integrate new data management and processing technologies to enhance analytics capabilities.
• Create and manage data repositories, following best practices for data governance and security.
• Develop documentation and provide training to team members on data systems and workflows.
• Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
• Stay updated on the latest industry trends and technologies in data engineering and machine learning.
• Lead the development and deployment of machine learning models that drive key business metrics and outcomes.
• Build and maintain scalable data pipelines and feature stores for training and inference use cases.
• Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery.
• Monitor and retrain models in production to ensure performance over time and handle data drift issues.
• Contribute to architectural decisions on data platforms and model-serving infrastructure.
• Mentor junior team members and help shape best practices in data science engineering.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline.
• 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions.
• Demonstrated experience translating business problems into data science projects with measurable outcomes.
• Prior experience working closely with business stakeholders to operationalize models and drive ROI.

Soft Skills:

• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills, both verbal and written, to convey technical concepts effectively.
• Ability to work collaboratively in a fast-paced team environment and manage multiple priorities.
• Motivated self-starter with a passion for learning and applying new technologies.

Faisalabad, Pakistan | Posted on 12/19/2024

We are seeking a skilled and motivated Data Scientist with 1-2 years of experience to join our growing team. The ideal candidate will work on analyzing complex datasets, building predictive models, and delivering actionable insights to support business decisions.

Responsibilities:

• Analyze large and complex datasets to identify trends, patterns, and insights.
  
• Develop and implement machine learning models to solve business problems.
  
• Perform data preprocessing, cleaning, and transformation.
  
• Collaborate with cross-functional teams to understand business needs and deliver data-driven solutions.
  
• Visualize data and create dashboards to present findings effectively.
  
• Document processes, methodologies, and outcomes for scalability and knowledge sharing.
  
• Stay updated with emerging trends and technologies in data science and machine learning.

• Bachelor's degree in computer science, data science, or a related field.
  
• Proven experience with data analysis and machine learning techniques.
  
• Proficiency in programming languages such as Python or R.
  
• Experience with data visualization tools like Tableau, Power BI, or Matplotlib.
  
• Familiarity with databases and query languages (e.g., SQL).
  
• Strong knowledge of statistical methods and predictive modelling.
  
• Excellent problem-solving and analytical skills.
  
• Strong communication and teamwork abilities.