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Mid-level data role, metro location, and broad skillset at a well-known pharma increases applicant competition.
Core data engineering skills are transferable but incentive compensation domain knowledge creates moderate industry specificity.
Explicit 3–6 years and mandatory SQL, Python, Databricks raise screening strictness to a moderate level.
Own day-to-day operations and continuous improvement of the Sales Crediting Platform, ensuring accurate and reliable sales crediting processing.
Develop, maintain, and optimize data pipelines, validations, and business rules supporting sales crediting; monitor platform performance and resolve production issues.
Partner with stakeholders to translate business changes into platform enhancements; support Incentive Compensation cycles including testing, validation, deployment, and automation initiatives.
3–6 years of experience in data engineering, data analytics, business intelligence, or similar technical roles.
Strong hands-on experience with SQL and Python; experience with Databricks or similar cloud data platforms.
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Technology, Business Analytics, Statistics, Mathematics, or related discipline.
Work Experience Required: 3–6 years relevant experience; Notice period: Not explicitly mentioned in the JD.
Experience designing and managing scalable data pipelines and analytics in cloud environments like Databricks.
Proficient in translating complex business rules (Incentive Compensation, sales crediting) into scalable technical solutions with data validation and automated processes.
Comfortable collaborating across cross-functional teams, handling multiple projects, and taking ownership for platform performance in a regulated, commercial operations environment.