Data Engineer

About the Role

• We're looking for a Senior Data Engineer to own the data layer for the U.S. product team at a U.S.-based AI-powered workforce intelligence platform. You'll be the first data hire in the U.S. — building and operating the pipelines that power core product features, AI capabilities, and customer analytics, while serving as the in-timezone data responder for enterprise customers.
• You'll work alongside a Head of Product, a Senior Product Designer, and a Senior Full Stack Engineer as part of a small, high-ownership U.S. team, reporting to the Head of Data in Sydney. If you bring data science capability on top of engineering — analytics, model evaluation, experimentation — there is scope to take on that work as well.

About You

• You have 5+ years in data engineering or backend systems with a strong data focus, and you've owned pipelines end-to-end in production environments.
• You've worked with ML or LLM pipelines, embeddings, or RAG systems — the product is AI-powered and you need to have built in this space.
• You're comfortable being the first and only data person in the room, making trade-offs, and handing off to a distributed team with complete context.
• You use AI coding tools (Cursor, Copilot, Claude Code) as a core part of how you build — this is a baseline expectation, not a bonus.
• You communicate clearly with engineers, product partners, and enterprise customers about data issues and trade-offs.

What You'll Be Doing

• Build and maintain data pipelines to ingest and process structured datasets — CSVs, spreadsheets, APIs, and event streams — with strong validation and error handling.
• Develop and operate pipelines supporting embeddings, RAG, and LLM-driven data workflows central to how the product functions.
• Serve as the U.S.-hours first responder for customer data issues — investigate, assess severity, and resolve directly or hand off to the Sydney team with full context.
• Build playbooks and observability tooling for data triage to compress response times and reduce cross-timezone back-and-forth.
• Partner with the Head of Product and engineering team to surface what the data can and can't support, and inform product direction.
• Deploy, monitor, and maintain data systems using Terraform and CI/CD pipelines in production.
• Contribute to consolidating AI-assisted development practices across the data stack.

What We're Looking For

• High ownership and comfort operating in ambiguous, fast-moving environments with a small team and no safety net.
• A proactive approach to customer issues — you investigate, document, and close the loop without waiting to be asked.
• Clear, direct communication across engineers, product, and customers.
• An AI-first mindset applied to how you build, not just what you build.

Technical Requirements

Must-Haves

• :
• 5+ years in data engineering or backend systems with a strong data focus.
• Strong Python skills for pipelines, data processing, and scripting.
• Strong SQL and experience with relational databases (PostgreSQL, MySQL).
• Experience building ETL/ELT pipelines and event-driven processing (queues, async workers, pub/sub).
• Hands-on experience with ML or LLM pipelines, embeddings, or RAG systems.
• Infrastructure comfort: Terraform, CI/CD, and AWS services (S3, RDS, EKS).

Nice-to-Haves

• :
• Data science capability: analytics, model evaluation, experimentation, or statistical analysis.
• Experience with structured ontology data or knowledge graphs.
• Prior startup or scale-up experience in a fast-moving environment.
• Customer-facing data work with enterprise clients.
• Experience working across time zones in a distributed team.