Data Analyst

Job description

Key Responsibilities  SQL Development o  Design, write, and optimize complex SQL queries using CTEs, window functions, multi-level joins, and subqueries across large pharmaceutical datasets. o  Read, interpret, and refactor extensive legacy SQL codebases (often spanning thousands of lines) to improve performance and maintainability. o  Develop reusable SQL modules and transformation logic following data engineering best practices.  Techno Functional Bridge o  Collaborate directly with stakeholders, field reimbursement teams to gather and translate functional requirements into technical specifications. o  Participate in requirement walkthroughs, data mapping sessions, and UAT (User Acceptance Testing) to ensure data solutions meet business intent. o  Document data flows, business logic embedded in SQL, and data dictionaries o  Proactively identify data quality issues and work with upstream data owners to resolve them.  Cross-Functional Collaboration & Communication o  Communicate clearly with both technical and non-technical stakeholders, adapting language and depth appropriately. o  Present data solutions, logic explanations, and pipeline designs in team meetings, and documentation. o  Work closely with BI developers to align data models with downstream consumption needs. Required Skills & Experience  Bachelor’s or Master’s degree in computer science, Information Systems, Statistics, or a related field.    4+ years of hands-on experience in data engineering or a techno-functional data role.  Demonstrated experience working with pharmaceutical or life sciences datasets.  Advanced SQL proficiency — CTEs (Common Table Expressions), window functions (ROW\\_NUMBER, RANK, LEAD/LAG, PARTITION BY), complex multi-table joins, correlated subqueries, and aggregations.  Ability to read, understand, and modify SQL scripts exceeding 1,000+ lines written by multiple authors.  Experience with SQL platforms such as MS SQL Server, Snowflake, PostgreSQL, Oracle, or similar.  Familiarity with data warehouse concepts: star/snowflake schemas, slowly changing dimensions (SCD), fact and dimension tables.  Experience with Power BI. Brownie points if worked on Tableau to Power BI migration