Summary
✨ AI‑Generated
An energy-sector technology organization is seeking a Data Platform Engineer to build and operate an AWS-based internal data platform that powers analytics and data products. You will create reusable templates, platform services, and engineering standards that enable domain teams to deliver production-ready pipelines quickly and safely. The role combines hands-on data engineering with platform engineering, emphasizing infrastructure as code, data contracts, observability, and developer autonomy.
Highlights
Build and operate an internal data platform supporting analytics and data products across an organization. Work hands-on at the intersection of platform and data engineering. Create reusable templates, golden paths, and platform services that accelerate delivery, while promoting autonomy, quality, observability, and reliable data practices.
Description
Your role
We are looking for a Data Platform Engineer to help us build and run the internal data platform that powers analytics and data products across Enovos.
Our platform is AWS-based (Redshift, S3, Airflow and dbt) with OpenMetadata providing cataloguing, lineage and data contracts, and everything managed as code through Terraform and GitLab CI.
Our conviction is simple: domain teams should be able to build and operate their own data products with safe autonomy: freedom within clear guardrails.
Your job is to make that possible.
You will build the golden paths, templates, platform services and standards that let teams go from idea to production pipeline in hours instead of weeks.
Ownership, quality, contracts and observability are built in by default rather than bolted on.
This is a hands-on engineering role at the intersection of platform engineering and data engineering.
You will spend part of your time building pipelines and data products alongside domain teams; Because we believe the best platform capabilities are extracted from real use cases, not designed in isolation.
Your tasks
You will:
• Build and maintain our golden paths: project templates, scaffolding, GitLab CI pipelines and Terraform modules that make the right way the easy way for new data pipelines and data products.
• Operate and evolve our core platform services: Airflow, dbt tooling, OpenMetadata and our self-service analytics layer, keeping them reliable, secure and up to date.
• Administer and tune Redshift: distribution and sort keys, workload management and access patterns, so that pipelines and dashboards stay fast as usage grows.
• Embed observability by default: work with our observability engineering team to bake OpenTelemetry instrumentation, alerting and runbook patterns into pipeline templates, so failures and SLA breaches are detected before consumers notice.
• Build data pipelines and data products hands-on with domain teams, then extract what you learn into reusable platform capabilities.
• Enable and support your internal customers: write documentation, contribute to our platform portal, onboard teams and gather their feedback to drive the platform roadmap.
• Champion a product mindset for the platform itself: measure adoption, reduce friction, and prioritise based on what internal teams actually need.
• Apply DevOps principles throughout: everything as code, reviewed, tested and deployed through CI/CD, with security and cost-efficiency in mind.
