Data Engineer / Data Architect
Role Overview
We are hiring a hands-on Data Engineer / Data Architect . We have a classic problem: several contact lists that don't agree, a CRM the sales team lives in, and no single source of truth. You will design the fix and build it yourself, from the data model through to a working system the sales team relies on. There is no tech lead above you. The data volume is small and the stack is modern, so this job is about thinking, not babysitting infrastructure. This is a remote, full-time role.
What You'll Do
- Design the data model and overall architecture: decide where the source of truth lives and how the CRM, email tool, website and data sources connect to it.
- Model contacts, companies and the relationships between them, including many-to-many relationships.
- Build clean ingestion pipelines from multiple data sources, APIs and the website, so new data can be added without creating duplicates.
- Deduplicate and merge records into one trusted base, with clear source-priority rules and a human review step for uncertain matches.
- Keep the central database and the CRM in sync both ways, without overwriting what users enter.
- Own data quality: enrichment, stale record detection and ongoing checks.
- Use AI and LLMs to clean, classify and match data where it helps, with guardrails where it matters.
- Document the system so it outlives any one person, and explain technical decisions to a non-technical executive in plain language.
What We're Looking For
- 4+ years in data engineering or backend development, with at least one system you designed end to end.
- Strong SQL and relational data modeling - you have designed schemas from scratch, not just queried them.
- Production experience with Postgres.
- Python for ETL scripts, API clients and data cleaning jobs.
- Real experience building REST or GraphQL API integrations, including auth, pagination, rate limits and webhooks.
- Proven experience keeping two systems in sync and handling conflicts.
- Hands-on deduplication and entity resolution using exact and fuzzy matching.
- Clear spoken English and the ability to work independently without a tech lead above you.
- At least 4 hours of daily overlap with US Eastern Time.
Nice to Have
- CRM data experience (HubSpot, Salesforce or similar), especially working with their APIs.
- Supabase.
- Automation tools such as n8n or Make.
- dbt or other analytics engineering tooling.
- Using LLMs in data pipelines (Claude, OpenAI APIs, MCP).
- Data enrichment providers (Apollo, Clay, People Data Labs).
- B2B sales data experience.
- Light BI (Metabase, Looker Studio).