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

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