Data Solutions Engineer

💻 What you’ll do
Own data migrations end-to-end. Work directly with government staff to understand their source systems, configure schema mappings and ingestion settings, run validations and dry-runs, and ensure accurate, complete data lands in GovWell.
Be the gatekeeper for data quality. Identify gaps, inconsistencies, and edge cases in legacy data before they become production problems. Make documented judgment calls within defined constraints — and prevent bad or unsafe data from ever reaching production.
Be the technical face of onboarding. Lead customer calls, clearly explain data requirements and tradeoffs, and guide agency staff through the transition from legacy systems to GovWell with calm confidence.
Make the process better as you run it. Use internal tools, templates, and playbooks to reduce time-to-launch and minimize manual work. Help build toward a future where migrations are predictable, repeatable, and fast.
Close the feedback loop with Product and Engineering. Document recurring issues, unmet assumptions, and tooling gaps encountered during migrations — helping the platform evolve based on what you see in the field.

🧠 Who you are
Required

2-4 years of hands-on experience in data migrations, ETL/ELT, technical implementations, or a closely related role working with messy, real-world production data.
Demonstrated ability to work directly in a Python codebase day-to-day (reading, debugging, and shipping changes via PRs) — ideally in a data/pipeline repo (e.g., Airflow DAGs, ingestion jobs, migration utilities).
Strong SQL proficiency used in practice for analysis, validation, reconciliation, and transformation work.
Experience translating ambiguous stakeholder requirements into concrete, testable migration/implementation plans (what we’re importing, what we’re not, and why).
Track record of operating in execution-heavy environments with high ownership and high attention to correctness (where mistakes create customer-facing trust issues).

Preferred

Experience with workflow orchestration and pipeline operations (Airflow, Dagster, Prefect, etc.), including interpreting logs, safe reruns, and handling large backfills/imports.
Experience with customer-facing implementation/onboarding work (especially where you need to explain constraints and tradeoffs to non-technical stakeholders).
Familiarity with geospatial data concepts or GIS tooling (e.g., ArcGIS, address/parcel data), or strong willingness to learn quickly.
Experience in B2B SaaS (or similarly complex product domains) where data correctness materially impacts user workflows.
Experience partnering closely with product/engineering teams to turn recurring operational pain into playbooks, tooling improvements, and system-level fixes.