Data Solutions Engineer
Own end-to-end data migrations for government agencies switching to GovWell's AI platform. Clean messy legacy data (SQL/Python), lead customer calls with non-technical staff, ensure high-quality production data, and drive process improvements.
About the job
Responsibilities
- Own data migrations end-to-end: work directly with government staff to understand source systems, configure schema mappings and ingestion settings, run validations and dry-runs, ensure accurate and complete data lands in GovWell.
- Act as gatekeeper for data quality: identify gaps, inconsistencies, and edge cases in legacy data; make documented judgment calls within constraints; prevent bad or unsafe data from reaching production.
- Serve as technical face of onboarding: lead customer calls, explain data requirements and tradeoffs, guide agency staff through transition from legacy systems.
- Improve the migration process: use and enhance internal tools, templates, and playbooks to reduce time-to-launch and minimize manual work.
- Close feedback loop with Product and Engineering: document recurring issues, unmet assumptions, and tooling gaps to help evolve the platform.
Requirements
- 2-4 years of hands-on experience in data migrations, ETL/ELT, technical implementations, or 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 for analysis, validation, reconciliation, and transformation.
- Experience translating ambiguous stakeholder requirements into concrete, testable migration/implementation plans.
- Track record of operating in execution-heavy environments with high ownership and high attention to correctness.
Nice-to-Haves
- 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 explaining 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.
Tech Stack
- SQL (core for validation, reconciliation, troubleshooting)
- Python (data workflows and automation)
- Airflow (data migration pipelines)
- PostgreSQL (core database)
- RedwoodJS, GraphQL, TypeScript, AWS (broader environment)
Skills
SQL, Python, Airflow, Postgres, ETL, ELT, Data Migration, Gis, AWS
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