Remote Document the existing flow, source interfaces, transformations, and failure modes during

Make source onboarding repeatable and reduce the validated backlog.

- Detect schema changes, apply quality checks, and investigate pipeline failures.
- Maintain matching-service interfaces and contribute to agreed ML/matching changes.
- Test embedding and indexing consistency, compatibility, and matching quality.
- Work with DevOps on logs and alerts for freshness, failures, throughput, latency, and cost.
- Maintain tests, deployment discipline, and runbooks for independent operation and recovery.
- Clarify requirements, report progress, and escalate unresolved legal decisions to the client.

5–8 years of experience owning production data pipelines, including failure investigation and

Strong SQL and PostgreSQL modelling skills, with practical Go orchestration and migration

Experience with APIs, batch and asynchronous processing, schema evolution, metadata, and

Working knowledge of idempotency, reconciliation,



and safe recovery or reruns.

• Production experience with vector search and embedding pipelines for search or matching,

including diagnosing input, embedding, indexing, and downstream quality issues.

- Cloud operation, automated testing, code review, and deployment discipline.
- Monitoring, alerts, runbooks, privacy-aware data modelling, and access controls.
- Experience on data pipelines supporting production search, matching, or ML products.
- Explicit communication and collaboration with Product, Engineering, and DevOps teams.
- Direct pgvector and Amazon Bedrock experience (strongly preferred).
- VoyageAI embedding integrations and embedding evaluation.
- Python data-processing experience.
- Entity resolution and search relevance experience.
- Recruitment Technology / HRTech experience and familiarity with recruitment data.

📌 Senior Data Services Developer (Chennai)
🏢 Sourcebae
📍 Chennai