Senior Data Engineer (Golang)_RJ

We are looking for Data Engineer/Golang. Details: Engagement: Full-time contract, 6 months to start, with a strong chance of extension Fully remote Monday to Friday, 8 hours a day, with overlap with the team’s core working hours Start: as soon as possible Tech stack Go (orchestration), PostgreSQL with pgvector, embedding models served through Amazon Bedrock. What you’ll do Take over the current ingestion flow and document how it works: sources, transformations, weak points and failure scenarios Automate ingestion, validation, deduplication and incremental updates, and turn onboarding of new data sources into a repeatable process Build safe recovery mechanisms (retries, checkpoints, replay and backfill, quarantine) so that no data is lost or duplicated Track record counts, metadata, source identifiers and data lineage; catch schema changes and run quality checks Support the interfaces of the matching service and take part in improving embeddings, indexing and match quality Set up monitoring and alerting together with DevOps (freshness, failures, throughput, latency, cost) Keep tests, deployment practices and runbooks in shape so the system can be run and recovered without you Apply the agreed rules on data consent, access, retention and deletion, and flag any open questions early Work closely with Product, Engineering, DevOps and ML specialists, keep the team updated on progress What we expect Proven ownership of production data pipelines, including debugging and recovering failures Strong SQL and PostgreSQL data modelling skills Practical experience with Go for orchestration and migrations Solid understanding of APIs, batch and async processing, schema evolution, metadata and lineage Experience with idempotent processing, reconciliation and safe reruns Hands-on work with vector search and embedding pipelines in production (search, matching or ML products) Ability to trace quality problems across inputs, embeddings, indexes and downstream results Cloud experience, automated testing, code review and disciplined deployments Monitoring, alerting, runbooks, privacy-aware data modelling and access control Hiring process CV review, technical interview, live coding session, final interview.