Data Engineer
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Requirements
• All downstream business operations depend on high-quality data. In this role, you will be a critical contributor to ensuring that data is accurate, timely, and actionable. • 1–3 years of experience in data engineering, analytics, or related technical roles. • Solid understanding of ETL/ELT concepts and data pipeline design. • Proficiency in SQL; Python experience is a plus. • Foundational understanding of healthcare data; experience with claims data is a plus. • Familiarity with modern cloud data platforms (e.g., Databricks, Snowflake). • Strong analytical and problem-solving skills with attention to detail. • Ability to work independently while collaborating effectively within a team.
Responsibilities
• Data pipelines: Design, build, and maintain data pipelines using SQL, Python, dbt and Databricks. • Data pipelines: • Data validation: Conduct regular data quality checks to ensure accuracy and integrity for downstream users. • Data validation: • Data troubleshooting: Proactively identify data issues and develop custom solutions. • Data troubleshooting: • Process Optimization: Monitor pipeline performance and tune processes to improve efficiency. • Process Optimization: • Cross-functional collaboration: Work with cross-functional teams to understand data requirements and incorporate them into the data framework. • Cross-functional collaboration: • Team engagement: Actively participate in discussions, offering input and feedback to drive continuous improvement. • Team engagement: