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Data Platform Engineer (m/f/n)

Encevo encevo.eu Open · verified Oct 24, 2026
Esch-sur-Alzette Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Encevo. Esch-sur-Alzette.

Pay not stated Data Platform Engineer salary

RoleData Engineering
SeniorityMid-level
LocationEsch-sur-Alzette
PostedSep 3, 2026 · 7w ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Create reusable project starters, CI workflows and Terraform modules so teams can launch data pipelines and products more easily
  • Keep Airflow, dbt, OpenMetadata and the self-service analytics layer dependable, secure and current
  • Tune Redshift distribution, sorting and workload settings to keep pipelines and dashboards responsive
  • Add telemetry, alerts and runbook guidance to pipeline templates, working with observability engineers to catch failures early
  • Build pipelines with domain teams, then turn lessons into platform features, documentation and onboarding support

What you bring

  • At least five years in data engineering, including hands-on work with production data platforms
  • At least three years in platform, DevOps or cloud engineering
  • A computer science or engineering degree, a related qualification, or equivalent professional experience
  • Strong Python and SQL, plus practical experience with Infrastructure as Code, CI/CD and Airflow operations

Who this fits

This hands-on mid-level role suits an engineer who enjoys building platform capabilities while working directly on data products with domain teams. You will support internal users and help shape the platform roadmap. The permanent role is based in Esch-sur-Alzette, Luxembourg, with hybrid working possibilities. English fluency is required.

From the employer

Department : Energy Business IT | Location : Esch-sur-Alzette | Contract : Permanent | Job Requisition N°20113


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.

Your profile

You have:

• A university degree in computer science, engineering or a related field, or equivalent professional experience.
• At least 5 years of experience in data engineering with strong hands-on exposure to data platforms in production.
• At least 3 years of experience in platform engineering, DevOps or cloud engineering,
• Strong Python and SQL skills, and solid understanding of data modelling and pipeline design.
• Notable experience with Infrastructure as Code and CI/CD, preferably Terraform and GitLab CI: you are comfortable building pipelines and modules that other engineers depend on.
• Practical experience with Airflow (deployment and operations, not only DAG authoring) and with dbt, or strong motivation to drive its adoption as a modelling standard.
• Experience with AWS data services, ideally Redshift, S3 and Glue Catalog.
• A platform mindset: you build for other engineers, you value paved roads over one-off heroics, and you measure success by what teams can do without you.
• A pragmatic, collaborative way of working: you prefer a reliable, well-understood solution over a clever one nobody can maintain.
• Fluent in English.

Nice to have (you do not need to have it all)


• Experience with a metadata platform (OpenMetadata, DataHub or similar), data contracts or data mesh concepts.
• Experience building internal developer platforms, self-service tooling or scaffolding.
• Experience with Kubernetes, containers or cloud-native workloads.
• Experience with observability practices: OpenTelemetry, SLOs, alerting, runbooks.
• Experience deploying and operating BI platforms (Superset or similar) including SSO integration (OIDC/Keycloak).
• Experience with streaming, event-driven architectures or API-based data integration.
• Experience in the energy sector or other regulated, data-intensive environments.


What success looks like


In this role, you will help us:

• Let domain teams create a new production-ready pipeline from a template in hours, not weeks; with documentation, guidelines and monitoring included by default.
• Run platform services (Airflow, Redshift, etc) reliably and predictably.
• Make our catalogue, lineage and data contracts trustworthy without manual effort.
• Grow platform adoption because teams want to use it, not because they are told to.
• Reduce time spent on undifferentiated plumbing across all data teams.


What we offer


“Together we build the future of Luxembourg’s energy transition”

• The opportunity to join a Group that actively shapes the energy transition in Luxembourg and the Greater Region
• A role with real ownership and impact, with the opportunity to shape observability practices from the ground up.
• A strategic position between Data Platform, IT operations and product teams.
• A modern technical environment with cloud, automation, telemetry and data platform topics.
• A multicultural and international working environment with continuous learning and development opportunities.
• A competitive salary with many additional benefits (e.g. pension plan, additional health insurance, meal vouchers, private parking, company restaurant, etc.) and hybrid working possibilities.


For external applications, a certified copy of your diploma as well as a recent copy of your criminal record will be requested after the first interview.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.