Senior Full-Stack Data Engineer

Eneco; Rotterdam; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

FlexBudget

8% holiday allowance

Bonus or profit sharing

Hybrid working (home/office/abroad)

Job summary

Eneco is seeking an embedded data engineer operating at the intersection of Data Engineering, Platform Engineering and Quantitative Analytics. You will build and productionize data solutions using Azure technologies and Databricks, turning prototypes into scalable data products while supporting the ongoing data platform migration.

You will collaborate with analysts and quantitative specialists to align business goals with engineering priorities, promote CI/CD, testing, and robust documentation,

Qualifications

• Experience building data pipelines in Azure cloud environments.
• Production-grade data products from analytical prototypes.
• Experience turning notebooks into scalable production solutions.
• Familiarity with testing, code reviews, and CI/CD practices.

Responsibilities

• Act as an embedded engineer within a business-facing analytics and quantitative team.
• Lead and support ongoing data platform migration initiatives.
• Design and maintain Azure-based data pipelines and data products.
• Convert analyst notebooks into tested production solutions.
• Deploy and monitor Azure Databricks workloads in production.
• Collaborate with analysts and quantitative specialists to translate business needs into scalable tech solutions.
• Advance development lifecycle with testing, CI/CD, automation, and documentation.
• Optimize data transformations, models and reporting workloads.
• Provide guidance to colleagues to adopt sustainable engineering practices.

Skills

Data engineering

Python

SQL

Business understanding

Tools

Azure Databricks

Spark

Delta Lake

Azure ADLS Gen2

Azure DevOps

Data Factory

Unity Catalog

CI/CD tooling

Job description

In this role within the energy trading domain, you' ll work at the intersection of Data Engineering, Platform Engineering and Quantitative Analytics. You' ll help turn analytical solutions into reliable, production-grade data products while contributing to the evolution of the data platform and engineering practices. Strong engineering goes hand in hand with understanding the business challenges behind the technology.

• Work at the intersection of Data Engineering, Platform Engineering and Quantitative Analytics within the energy trading domain.
• Build and productionize data solutions using Azure, Databricks, Python, SQL and Spark across batch and streaming workloads.
• Help transform analytical prototypes into scalable, reliable and maintainable data products while supporting the wider data platform migration.

Why choose Eneco?

The One Planet strategy at Eneco sets an ambitious goal to be climate neutral by 2035. In this role, you' ll contribute from within the energy trading domain, helping turn analytical solutions into reliable, production-grade data products while contributing to the evolution of the data platform and engineering practices.

What you' ll do

• Act as an embedded engineer within a business-facing analytics and quantitative team.
• Lead and support the team through ongoing data platform migration initiatives.
• Design and maintain reliable Azure-based data pipelines and data products.
• Convert analyst-developed Python notebooks into tested, maintainable production solutions.
• Deploy, monitor and support Azure Databricks workloads in production.
• Work closely with analysts and quantitative specialists to understand business objectives and translate them into scalable technical solutions.
• Help professionalize the development lifecycle through testing, CI/CD, automation, monitoring and documentation.
• Optimize data transformations, models and reporting workloads.
• Provide technical guidance and help colleagues with varying levels of engineering maturity adopt sustainable engineering practices.

Is this about you?

You have:

• A strong Data Engineering background in Azure cloud environments.
• Hands-on Azure Databricks experience, including Spark, Delta Lake, Workflows and Unity Catalog.
• Strong Python and SQL skills.
• Experience building batch and streaming data pipelines.
• Experience turning notebooks and analytical prototypes into production-grade solutions.
• Knowledge of testing, code reviews, CI/CD and software engineering best practices.
• Experience working directly with analysts, data scientists, quantitative specialists or business-oriented teams.
• A strong ability to balance business understanding with technical execution.
• Experience with Azure services such as ADLS Gen2, Azure DevOps, Key Vault, Data Factory or equivalent.
• Experience contributing to platform migration or modernization initiatives.

Nice to have:

• Machine Learning Engineering or MLOps experience.
• Terraform or Bicep.
• Azure monitoring and observability tooling.
• DataOps practices and orchestration frameworks.
• Dashboard performance optimization and semantic modeling.

This is where you' ll work

You' ll be part of a business-facing team within the energy trading domain, working at the intersection of Data Engineering, Platform Engineering and Quantitative Analytics. You' ll work closely with analysts and quantitative specialists to understand business objectives and translate them into scalable technical solutions.

The environment is built around Azure and Azure Databricks, with the team developing and maintaining data pipelines and data products while progressing through an ongoing data platform migration. An important part of the work is strengthening engineering practices across testing, CI/CD, automation, monitoring and documentation.

What we have to offer

FlexBudget

Including FlexBudget, 8% holiday allowance, and depending on your role a bonus or collective profit sharing. Have it paid out, use it to buy extra holiday days or save it up for something nice, it's up to you.

Personal and professional growth

Eneco is fully committed to help you in your personal and professional development.

Hybrid working: home, office or abroad

Work 40% at the office, 40% from home, and 20% flexibly. With manager approval, you may work abroad (within approved countries) up to 3 weeks/year, max 2 consecutively.