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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Engineer, Data Platform - **Company:** Qualified Health - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $215,000 - $235,000 - **Contract:** Permanent contract - **Skills:** Unity 3d, Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Data Infrastructure, Software Design Documents, Python (Programming Language), Operational Databases, Performance Tuning, Search Technologies, SQL Databases, Strategies of Testing, Management of Software Versions, AI Infrastructure, Fast Healthcare Interoperability Resources, Large Language Models, Claude Code, Snowflake, Apache Spark, Electronic Medical Records, AI Coding Agents, Agentic-AI, Microsoft Fabric, Data Lakes, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Health Level Seven International, Machine Learning Operations, Terraform, Data Pipelines, Databricks - **Published:** November 14, 2026 - **Apply:** https://startup.jobs/senior-staff-engineer-data-platform-qualified-health-pbc-10765532 ## About the Role * Bachelors Degree in Computer Science, Electrical Engineering, Mathematics or a related field * At least 12+ years of software or data engineering experience, with a track record of designing and operating production data platforms at scale and of setting architecture across multiple teams. * Experience working in a highly regulated domain (Healthcare, Insurance, Finance) is required * Deep, hands-on expertise with Databricks is highly preferred but expertise in Snowflake or Microsoft Fabric would be aligned as well. + Experience with the lakehouse stack: Spark, Delta Lake, Unity Catalog, Workflows or equivalent, and performance and cost tuning at scale. * Experience building pipelines for ML or LLM applications, such as LLM-based extraction, embeddings and vector search, feature pipelines, or evaluation datasets. * Fluency in Python and SQL, with sound software engineering practices: testing, CI/CD, infrastructure as code, and code review. * Demonstrated practical use of agentic coding tools (such as Claude Code or similar) in real delivery work, and good judgment about when to trust, verify, and constrain them. * Experience owning ambiguous, cross-team problems end to end and influencing without direct authority. * Clear written and verbal communication, including authoring design docs that others build from., * Experience with healthcare data: claims, EHR, FHIR or HL7, and HIPAA-compliant handling of PHI. * Databricks certifications or experience with Delta Live Tables, Lakeflow, or Databricks Asset Bundles. * Experience with other orchestrators (Airflow, Dagster, Prefect) and a view on when each is the right tool. * Experience with cloud infrastructure (GCP, AWS, or Azure), Terraform, and Kubernetes. * Contributions to open-source data, workflow, or AI infrastructure projects. ## Description We are hiring a Senior Staff Engineer to set the technical direction for the Data Platform and to build it hands-on. Databricks is the center of the role: you will own the architecture of our lakehouse and the data pipelines, governance, and performance that run on it. In addition, you will build and run the AI pipelines that sit alongside it, using Temporal for durable orchestration. You will work across product, AI, and engineering pods, and you will raise the bar for how the whole team builds, including how we use AI coding agents to ship faster and with higher quality., * Own the lakehouse. Architect and evolve our Databricks lakehouse, including medallion layering (bronze, silver, gold), Delta Lake, Unity Catalog governance, and workspace and compute strategy. * Build and tune Databricks pipelines. Design, build, and optimize Spark and SQL pipelines on Databricks, including incremental processing, data quality enforcement, performance tuning, and cost management. * Make data trustworthy. Define data contracts, quality checks, access controls, and PHI-aware governance in partnership with security and compliance. * Power AI and LLM workloads. Build the data foundations for AI products: LLM-ready datasets, retrieval and vector-store pipelines, evaluation data, and the interfaces that let AI and product teams consume governed data safely. * Build AI pipelines on Temporal. In addition to Databricks, design durable workflows on Temporal for AI pipelines: scheduled and watermarked pulls from Databricks gold tables, file-ingestion workflows, and long-running LLM extraction and enrichment jobs. Establish patterns for retries, idempotency, versioning, and backfills, and keep the handoff between Databricks and Temporal clean, observable, and well governed. * Lead agentic engineering. Use AI coding agents daily and define how the team does agentic development: tooling, prompts, guardrails, code review practices, and test strategy for agent-written code. * Set technical direction. Write and review technical designs, set platform-wide standards, and make build-versus-buy decisions that hold up over multiple years. * Multiply the team. Mentor engineers across teams, unblock other pods, and communicate trade-offs clearly to technical and non-technical stakeholders.