Senior Data Engineer (Sql – Essential)

We are looking for a Senior Data Engineer (Level 1) to help lead the design, build, and operation of the data pipelines and platform capabilities that underpin analytics, billing, experimentation, AI/ML workloads and commercial reporting across the organisation. This is a hands-on, ownership-focused role within a modern cloud-native data platform. You will take end-to-end responsibility for one or more domains, set technical direction within your area, and raise the bar for engineering quality across the team. Alongside your delivery work, you will mentor Level 1 and Level 2 engineers and act as a trusted partner to analytics, platform, and product stakeholders.

KEY RESPONSIBILITIES

• 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

TECHNICAL REQUIREMENTS

• 5–9 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