Data Pipelines:

• Design, develop, and manage data pipelines of varying complexity, ensuring smooth flow from acquisition sources to integration and consumption for key stakeholders like business analysts, data scientists, etc.
• Ensure compliance with data governance and security standards while operationalizing data pipelines, collaborating effectively with platform engineers and database administrators.
• Implement best practices for agile development, facilitating seamless updates from development to production environments.
• Support upgrades and testing initiatives as needed, exploring additional data extraction and analysis options from source systems to meet diverse customer needs.
• Develop solutions to enhance data analytic capabilities without disrupting transactional systems.

Metadata Management & Data Modeling:

• Create and implement data models to support organizational strategies, working closely with stakeholders to ensure scalability and efficiency.
• Document data models and extraction processes for reference by team members and customers, leveraging modern tools and techniques to automate repetitive tasks and improve productivity.
• Continually refine solutions to deploy best practices across reports, database structures, and extraction methods, collaborating with vendors as necessary.
• Address complex reporting requests and contribute to deeper understanding of source system data models.

Technical & Business Skill:

• Demonstrate proficiency in Data Management practices and architectures such as Data Modelling, Data Warehousing, Data Lake, etc., with foundational knowledge of others.
• Proficiency in Python and Pyspark for forward-looking data processing and analysis.
• Experience with SSIS or other ETL tools for data extraction, transformation, and loading.
• Flexibility with ETL tool experience, demonstrating adaptability to different technologies and systems.
• Understand core clinical, business, and research processes to develop tailored data solutions, obtaining relevant certifications as needed and pursuing continuous education.

Project Execution & Management:

• Execute project tasks efficiently with a focus on quality, communicating status effectively using project management tools.
• Participate actively in project meetings and serve as technical lead for moderately complex projects, ensuring effective management of scope, risk, and budget.
• Provide technical support and customer service, ensuring adherence to Service Level Agreements and promoting change management policies.
• Collaborate closely with stakeholders, particularly data science teams and business analysts, to refine data requirements and support data consumption needs.