Senior Data Engineer (AI-Native) — Data Layer

• 7+ years hands-on as a data engineer with real, demonstrable production ownership — pipelines and data models serving real users at scale.
• Strong fundamentals. You understand what your code and your queries are doing and why. You can read a query plan, reason about a slow or expensive pipeline, and debug a data-correctness bug to its root.
• Strong programming and SQL skills. You build efficient pipelines, schemas, and queries, and can model data for both transactional and analytical access patterns.
• Hands-on orchestration experience, building reliable ingestion/ELT pipelines against messy upstream sources.
• Experience with a cloud data warehouse and a major cloud platform.
• Experience ingesting from multiple source types: file-based, event/streaming, and API-based.
• Solid grasp of data-consistency failure modes — partial loads, late or out-of-order data, idempotency, backfills, schema drift.
• Daily, hands-on use of agentic dev tools (Claude Code, Cursor agent mode, Codex, or equivalent) to ship real work. You can talk concretely about how you structure prompts, manage context, parallelize agents, and verify their output.
• Ownership and judgment. You take data systems from idea to production and exercise good taste on what to build and what to cut.
• Startup mindset and strong communication — pragmatic, fast, biased to ship, and able to explain data decisions to engineers, PMs, and customers in writing.
• English at C1 or above.

Big Plus

• Deep cloud data warehouse experience and modern transformation tooling.
• Streaming / event ingestion at scale.
• Medallion or lakehouse architecture experience on large, multi-source data.
• Experience integrating enterprise sources such as ERP (Epicor Eclipse, Prophet 21) or ecommerce systems, and reconciling messy transactional data.
• Building data systems that feed AI/ML or agentic products — serving/feature layers, retrieval, or data contracts for model inputs.
• Prior experience at an early-stage SaaS startup.

Originally posted on Himalayas