SENIOR DATA ENGINEER (SQL â Essential)
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Summary
Senior data engineer who owns ELT pipelines, Snowflake modelling, data quality/observability standards, and production support end to end, while mentoring junior engineers. Core stack: SQL, Python, Snowflake, dbt, AWS/Azure, Terraform and CI/CD.
KEY RESPONSIBILITIES:
Should you not hear from us within 14 days then please consider your application as unsuccessful.
- Owning the design, development, and long-term operation of ELT pipelines and curated data products across one or more domains
- Setting the modelling approach across staging, intermediate, and data mart layers in Snowflake, and ensuring reusable, well-tested patterns are followed by the team
- Leading the data ingestion and exposure of new data sources for major products, features, and business initiatives, from discovery through to production
- Defining and evolving data quality, monitoring, and observability standards used across the team
- Driving cost efficiency, query performance, and storage optimisation within Snowflake, including warehouse strategy, clustering, and access patterns
- Owning schema evolution, data lineage, and documentation for your domain, and setting the expectation for how these are handled across the platform
- Contributing to platform standards, tooling, and architectural direction alongside Lead Engineers and the Platform team
- Leading production support for your domain, including on-call rotation, incident response, and postmortems
- Mentoring Level 1 and Level 2 engineers through code review, pairing, and technical guidance, and supporting their growth
- Partnering with Analytics Engineers, Data Analysts, Data Scientists, AI/ML Engineers, Platform Engineers, and Software Engineers to shape and deliver end-to-end data solutions
- Championing automation and AI-assisted development techniques to improve pipeline quality, documentation, and delivery speed
- Continuously evaluating modern data and AI-driven approaches, and influencing those that are invested in
- 59 years experience in data engineering, with a track record of owning production systems end-to-end
- Deep SQL and strong Python experience, with the ability to design as well as build data pipelines
- Substantial hands-on experience with Snowflake, including query profiling, warehouse strategy, RBAC, cost management, clustering, and performance tuning
- Advanced dbt experience, including custom macros, packages, incremental strategies, testing frameworks, and multi-project or mesh patterns
- Solid experience with cloud platforms, particularly AWS (and / or Azure), including core services such as S3, Lambda, IAM, and networking fundamentals
- Fluency within a mature SDLC, including Infrastructure as Code (Terraform), CI/CD pipelines, and Git-based collaboration
- Experience with data orchestration tools (Openflow or similar) at a design and standards-setting level
- Demonstrated experience designing and operating data quality, observability, and monitoring frameworks in production
- Track record of mentoring engineers and raising the technical standard of a team
- Ability to lead technical discussions with engineering, analytics, and business stakeholders and translate ambiguity into a plan
- Experience leading a migration or modernisation initiative from a legacy platform onto a modern cloud data stack
- Experience designing platform-level patterns (data contracts, shared macros/packages, reference architectures)
- Familiarity with analytics, experimentation, or AI/ML data workloads operating at scale
- Exposure to regulated data domains (iGaming, financial services, healthcare) and their compliance requirements
- Contributions to open-source tooling, technical writing, conference talks, or internal engineering communities
Should you not hear from us within 14 days then please consider your application as unsuccessful.
