Senior Full Stack Engineer (Data, AI)

Job Description Key Responsibilities ·       Own end-to-end design and delivery of data pipelines, from ingestion to transformation to serving ·       Design data models and storage architectures that support both operational and analytical workloads ·       Build and maintain infrastructure for data quality, observability, and governance ·       Contribute to broader product and platform architecture, working alongside other software engineers as priorities shift ·       Design systems that are extensible enough to support AI/retrieval-based features over time ·       Contribute significantly to key technical decisions, escalating trade-offs where they intersect with broader priorities ·       Collaborate with stakeholders on platform and deployment decisions ·       Work with attention to data sensitivity and system constraints in a regulated environment Qualifications Technical Requirements Required ·       5–7+ years of professional software engineering experience, with demonstrated ownership of production data systems end-to-end ·       Strong data engineering fundamentals: ETL/ELT pipeline design, data modeling, batch and streaming processing ·       Strong proficiency in at least one general-purpose programming language, with a track record of building production-grade backend systems, not just data scripts or pipelines ·       Solid software engineering fundamentals: API design, system architecture, ability to work across the stack when needed ·       Experience working with cloud-native data platforms or lakehouse architectures ·       Comfortable operating with significant autonomy and taking a leading role in technical decisions ·       Strong communication skills; able to explain technical trade-offs to non-technical stakeholders Good to have: ·       Experience with Databricks, Unity Catalog, Delta Lake, or similar lakehouse tooling ·       Experience building data pipelines to support retrieval-augmented generation (RAG) or other AI/ML workflows, e.g. embedding generation, vector store population ·       Experience in government, public sector, or other regulated environments with data sensitivity requirements ·       Experience with cloud-native deployment platforms