Quick Overview
Job Description
hackajob is collaborating with Version 1 to connect them with exceptional professionals for this role.
We are looking for a Senior Data Engineer to join Version 1's Data & AI Practice, working on modern data platforms for enterprise and regulated clients. You will be a hands on engineer with strong production experience, contributing to the design, build, and operation of scalable, cloud native data solutions that enable analytics and AI at scale.
This is a delivery focused role for an experienced engineer who enjoys solving complex data challenges, takes ownership of outcomes, and applies strong engineering discipline in real world environments.
What You'll Be Doing
- Designing, building, and operating reliable data pipelines using modern ETL/ELT approaches
- Engineering cloud native data platforms, primarily on AWS (with Azure exposure where required)
- Working with technologies such as Databricks, PostgreSQL, Aurora, and distributed processing frameworks
- Ensuring solutions are production ready: secure, tested, observable, and cost efficient
- Optimising data performance, reliability, and data quality in live environments
- Collaborating with analysts, data scientists, AI engineers, and platform teams
- Mentoring junior engineers and contributing to shared standards and accelerators
Qualifications
What You'll Bring
- 6-8 years' experience in hands on data engineering roles
- Strong Databricks experience (Data Engineering, Delta Lake, Medallion Architecture)
- Design, build and support scalable data pipelines from enterprise source systems
- Build and maintain data models, mapping tables and curated data products within the ISP data platform
- Implement Master Data Management (MDM), data quality controls, monitoring and remediation workflows
- Develop automated data quality and completeness reporting, including AI-assisted reporting capabilities
- Support the industrialisation of AI-enabled applications, transitioning from file-based solutions to governed Databricks-backed data services
- Experience integrating AI/analytics tools with enterprise data platforms and supporting operationalisation of proof-of-concepts into production solutions
Nice to Have
- Experience enabling ML, AI, or GenAI workloads through strong data foundations
- Exposure to modern BI and analytics tooling
- Experience working in regulated or security conscious environments
- Consulting or client facing delivery experience
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