Databricks Data Engineer

Empresa: Axpo Group
Provincia: hibrido
Población: 

Descripción: 
Who We Are

Axpo is driven by a single purpose – to enable a sustainable future through innovative energy solutions. As Switzerland´s largest producer of renewable energy and a leading international energy trader, Axpo leverages cutting-edge technologies to serve customers in over 30 countries. We thrive on collaboration, innovation, and a passion for driving impactful change.

About the Team

You will report directly to our Head of Development and join a team of highly committed IT data platform engineers with a shared goal: unlocking data and enabling self-service data analytics capabilities across Axpo. Our decentralized approach means close collaboration with various business hubs across Europe, ensuring local needs shape our global platform. You´ll find a mindset committed to innovation, collaboration, and excellence.

What You Will Do

As a Databricks Data Engineer, you will:
– Be a core contributor in Axpo´s data transformation journey by using Databricks as our primary data and analytics platform.
– Design, develop, and operate scalable data pipelines on Databricks, integrating data from a wide variety of sources (structured, semi-structured, unstructured).
– Leverage Apache Spark, Delta Lake, and Unity Catalog to ensure high-quality, secure, and reliable data operations.
– Apply best practices in CI/CD, DevOps, orchestration (e.g., Dragster, Airflow), and infrastructure-as-code (Terraform).
– Build re-usable frameworks and libraries to accelerate ingestion, transformation, and data serving across the business.
– Work closely with data scientists, analysts, and product teams to create performant and cost-efficient analytics solutions.
– Drive the adoption of Databricks Lakehouse architecture and help standardize data governance, access policies, and documentation.
– Ensure compliance with data privacy and protection standards (e.g., GDPR).
– Actively contribute to the continuous improvement of our platform in terms of scalability, performance, and usability.

What You Bring and Who You Are

We´re looking for someone with:
– A university degree in Computer Science, Data Engineering, Information Systems, or a related field.
– Strong experience with Databricks, Spark, Delta Lake, and SQL/Scala/Python.
– Proficiency in dbt, ideally with experience integrating it into Databricks workflows.
– Familiarity with Azure cloud services (Data Lake, Blob Storage, Synapse, etc.).
– Hands-on experience with Git-based workflows, CI/CD pipelines, and data orchestration tools like Dragster and Airflow.
– Deep understanding of data modeling, streaming and batch processing, and cost-efficient architecture.
– Ability to work with high-volume, heterogeneous data and APIs in production-grade environments.
– Knowledge of data governance frameworks, metadata management, and observability in modern data stacks.
– Strong interpersonal and communication skills, with a collaborative, solution-oriented mindset.
– Fluency in English.

Technologies You´ll Work With
– Core: Databricks, Spark, Delta Lake, Python, dbt, SQL
– Cloud: Microsoft Azure (Data Lake, Synapse, Storage)
– DevOps: Bitbucket/GitHub, Azure DevOps, CI/CD, Terraform
– Orchestration and Observability: Dragster, Airflow, Grafana, Datadog, New Relic
– Visualization: Power BI
– Other: Confluence, Docker, Linux

Nice to Have
– Experience with Unity Catalog and Databricks Governance Frameworks
– Exposure to Machine Learning workflows on Databricks (e.g., MLflow)
– Knowledge of Microsoft Fabric or Snowflake
– Experience with low-code analytics tools like Dataiku
– Familiarity with PostgreSQL or MongoDB
– Front-end development skills (e.g., for data product interfaces)

Department Installation / Maintenance / Servicing / Craft Locations Madrid Remote status Hybrid
Tecnologías: Spark, Databricks, Python, SQL, Scala
Tipo de Contrato: 
Indefinido
Salario: Sin especificar
Experiencia: 3 años
Funciones: Big Data
Descubre más: https://www.tecnoempleo.com/databricks-data-engineer-axpo-group/spark-python/rf-0386153972bae3c55b4d


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