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Dev done better. Perform offers expert engineering consulting and staffing for the most demanding products.
Senior Data Engineer
Location
United States
Posted
95 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Engineer
Perform
• Own the Data Platform • Design, build, and operate MDVIP’s data platform on Azure Databricks—ingestion, transformation, storage, and serving layers that power analytics, AI models, and operational reporting. • Build and maintain data pipelines across MDVIP’s ecosystem: Salesforce, SQL Server, Snowflake, third-party sources, and the new cloud-native payments platform. • Engineer for quality and trust—validation checks, anomaly detection, lineage tracking, and documentation that ensure every downstream consumer can rely on the data. • Write clean, version-controlled, production-grade code. • Think like a software engineer building a product, not a script runner maintaining jobs. • Go Deep Into the Business Domain • Partner directly with business stakeholders across physician growth, member services, finance, and operations to understand how data drives decisions—then build for those decisions, not for abstract requirements. • Act as a technical product owner for your domain areas: own the backlog, prioritize based on business impact, and ship iteratively without waiting for a PM to sequence your work. • Translate ambiguous business questions into data models, feature tables, and curated datasets that analysts and data scientists can build on immediately. • Close the loop—follow your data through to the dashboard, the model, or the operational workflow and validate that it’s actually driving the outcome. • Drive AI-First Engineering Practices • Use Claude Code and agentic development as your primary workflow—AI-driven pipeline generation, automated testing, rapid prototyping—to ship at a pace that would be impossible with traditional approaches. • Build data infrastructure that is AI-ready: well-documented, semantically clear, and structured so that AI tools and agents can reason over it effectively. • Scout, evaluate, and adopt emerging AI tools and platforms that make the data team faster—separating real value from hype with hands-on testing. Share what you learn. Document patterns, run demos, and help the broader team adopt AI-first workflows with confidence.
Job Requirements
- BS in Computer Science, Data Science, or related field; 6+ years in data engineering or a hybrid data engineering/analytics role.
- Deep hands-on experience with Azure Databricks—notebooks, Delta Lake, Unity Catalog, and production-scale pipelines.
- Strong Python and SQL; experience with PySpark and distributed data processing.
- Built and operated data pipelines that serve analytics, ML models, and operational systems—not just batch ETL jobs.
- Worked directly with business stakeholders to define requirements, shape data products, and deliver measurable outcomes.
- Active, daily use of AI coding tools (Claude Code, Copilot, or similar) as a force multiplier.
- Strong communication skills with a track record of presenting technical work to non-technical audiences.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
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