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About the role
Education: • Bachelor’s degree in Computer Science, Computer Engineering, Data Analytics, Business Analytics, or a relevant field. Required Experience: • 3+ years of experience in a Data Analyst, Business Analyst, BI Analyst, or similar role. • Professional experience working with life science domain • Demonstrated experience working in a software/data development lifecycle (e.g., requirements, acceptance criteria, UAT support). • Strong ability to translate stakeholder needs into clear, testable requirements and communicate effectively with technical teams. • Strong SQL skills and experience working with large datasets. • Familiarity with modern data environments and tooling (e.g., Databricks, ETL/ELT concepts, Azure, ADF, Python). • Experience with governed data environments and well-defined metric/rule management practices. Preferred Qualifications: • Experience with Spark/Delta optimization (partitioning, file sizing, performance tuning). • Experience in healthcare/Life Sciences is preferred but not required. • Knowledge/experience in DevOps and Agile methodologies.
Technical Skills: • Strong SQL skills for data querying, transformation, and validation • Familiarity with Azure Databricks, Azure Data Factory (ADF), and modern cloud data platforms • Understanding of ETL/ELT concepts and data pipeline workflows • Experience with data visualization and reporting tools (e.g., Power BI, Tableau) • Familiarity with Python for data analysis and scripting • Understanding of governed data environments, Unity Catalog, and metric/rule management • Knowledge of data quality frameworks and validation methodologies • Familiarity with version control (Git) and collaborative development workflows Knowledge, Skills & Abilities: • Strong analytics and problem-solving skills with experience across a broad spectrum of analytics • Strong written and verbal communication skills • Ability to translate complex business needs into clear, structured, and testable requirements • Strong team player working on cross-functional deliverables • Attention to detail with a focus on data accuracy and consistency
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