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.