Data Solutions Engineer

Data Solutions Engineer

When a city switches to GovWell, one thing has to go right before anything else can: their data. A decade of permits, parcels, inspections, and license records — often living in a 2009 Access database, a folder of CSVs, or a legacy system with no documentation — has to land in GovWell accurately. If it doesn't, our relationship with a new client is off to a bumpy start.

As a Data Solutions Engineer, you own that moment. You'll take whatever a city hands you — messy exports, inconsistent codes, half-mapped schemas, geospatial data of questionable quality — and turn it into clean, trusted production data. That means writing SQL/Python that finds the edge cases before they find you, leading calls with non-technical government staff, and making judgment calls on messy data that you'd stake the launch on.

You'll report directly to Ben Cohen (Co-Founder & CTO) and work across Deployment, Product, and Engineering — with real influence over how GovWell's onboarding process matures as we scale.

We have a hybrid work culture that combines regular in-person collaboration at our New York City office (3+ days per week) with flexibility to work remotely.

What You'll Do

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

Our Tech Stack

• SQL – your core tool for validation, reconciliation, and troubleshooting

• Python – used in data workflows and automation

• Airflow – for managing data migration pipelines

• PostgreSQL – our core database

• RedwoodJS, GraphQL, TypeScript, AWS – the broader software engineering environment you'll interact with

Compensation and Benefits

Compensation within the posted salary band will be commensurate with experience. All offers will include:

• Competitive base salary.

• Equity / stock options.

• Medical, dental, and vision insurance.

• 401(k) program.