Staff Data Engineer

Interwell Health is a kidney care management company dedicated to reimagining healthcare. The Staff Data Engineer will serve as a senior technical leader responsible for shaping and governing the data ecosystem, delivering high quality data products that enhance clinical and operational outcomes.

Responsibilities:

• Design and evolve a scalable, secure, cloud‑native lakehouse platform leveraging Databricks, Microsoft Fabric (OneLake, Lakehouse, Data Factory), and dbt
• Define modeling patterns, governance frameworks, and engineering best practices across the data lifecycle
• Lead design reviews and guide teams in adopting scalable architectural patterns
• Drive long‑term platform strategy and evaluate emerging technologies
• Design and implement batch and streaming data pipelines for healthcare data sources (EHR, claims, HL7/FHIR, APIs, flat files, databases)
• Develop modular ingestion, quality, lineage, metadata, and observability frameworks that scale across domains
• Produce clean, analytics‑ready datasets and data models for BI, analytics, and machine learning workloads
• Implement HIPAA‑aligned access patterns and secure handling of PHI
• Architect Databricks workloads (clusters, jobs, Unity Catalog, Delta Lake) for reliability, performance, and cost efficiency
• Integrate Databricks and Microsoft Fabric with Azure services and enterprise systems
• Partner with product managers, data scientists, analysts, clinicians, and business stakeholders to translate healthcare data needs into scalable solutions
• Lead Cross functional initiatives that modernize and unify the organization’s data ecosystem
• Mentor senior and mid-level engineers; elevate team capability through technical coaching and standards
• Drive roadmap planning, platform evolution, and long-term data strategy
• Champion engineering excellence, reliability practices, documentation quality, and governance

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field
• 7+ years of experience in data engineering
• 2+ years operating in a senior or staff level engineering role
• Deep hands-on proficiency with Databricks, Spark, Delta Lake, dbt, and Python
• Proven ability to design and operate largescale cloud data platforms (Azure preferred)
• Hands on experience with Data Engineering, Data Factory, Lakehouse, OneLake
• Advanced data platform architecture and Lakehouse design expertise
• Demonstrated ability to design modular, extensible frameworks and guide the long-term evolution of enterprise data platforms
• Strong command of distributed data processing and cloud native engineering
• Experience working in HIPAA regulated environments and handling PHI
• Healthcare data fluency, including regulated data handling and compliance
• Technical leadership, mentorship, and influence across teams
• Strong communication skills with both technical and clinical stakeholders
• Experience with platform reliability, CI/CD for data pipelines, and infrastructure as code
• 100% remote (ET or CT work hours preferred)
• Experienced in implementing and supporting Epic integrations, leveraging Cogito Cloud and Caboodle data models, and delivering reliable incremental data pipelines from Caboodle/Clarity