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We're hiring a Senior Data Engineer to own our data platform and build the infrastructure supporting operational analytics, governance, and emerging AI capabilities. If you love designing elegant data systems, thrive with autonomy, and want to make a meaningful impact at scale, this role is for you.
You’ll work end-to-end on data pipeline architecture, design systems that scale, and collaborate with product and engineering teams to ensure data quality, security, and performance. This is a high-ownership role where you’ll shape technical decisions, mentor through collaboration, and contribute to broader platform architecture.
This is a fixed-term contract role, 12 months engagement.
What You’ll Do
- 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
What We’re Looking For
- 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
- 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
Bonus
- 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 (embedding generation, vector store population)
- Experience in public sector or other regulated environments with data sensitivity requirements
- Experience with cloud-native deployment platforms
- Relevant technical certifications or technical assessment scores with dates