Senior Software Engineer - Databricks Data Engineering & Analytics (part-/full-time)

Deutsche Börse AG
Leipzig, Germany
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
1 year minimum
Working hours
Regular working hours
Languages
English, German

Tech stack

Amazon Web Services Microsoft Azure Cloud Computing Code Review Continuous Integration Data Architecture Information Engineering Extract Transform Load (ETL) Database Development DevOps Distributed Systems Apache Hive
+16 more
Python (Programming Language) Performance Tuning Standard Sql SQL Databases Google Cloud Apache Spark Backend Git Build Management Data Lakes Pyspark Data Analytics Software Version Control Data Pipelines Legacy Systems Databricks

Job description

This role as “Senior Software Engineer (f/m/d) - Databricks Data Engineering & Analytics” in our team “Data Development” is an opportunity to do more than contribute your technical expertise. You will take ownership of data engineering and play a key role in shaping the culture, standards, and practices of a growing team. As a catalyst for change, you will not simply fill an existing gap. You will raise the capabilities of the entire team and organization, creating an impact that is multiplicative rather than additive. You will work with Databricks from your first day, building on a modern, cloud-native platform instead of maintaining legacy systems. With dedicated teams responsible for infrastructure, platform engineering, and DevOps, you can concentrate on what you do best: advancing data engineering and mentoring your colleagues. The purpose behind this work is equally significant. ECC’s data is mission-critical for European energy markets, meaning your contribution will help ensure that homes stay warm and that Europe can successfully move towards a green future. Our tools:

  • Primary tech stack: Google Cloud Platform (Databricks), Apache Spark, Python, SQL, Delta Lake
  • Orchestration: Databricks Workflows
  • Data patterns: Medallion architecture, lakehouse design
  • Governance: Unity Catalog
  • Your platform is managed centrally by Deutsche Börse - you focus on data engineering and eventually on empowering business users, not on infrastructure or DevOps.

Your tasks:

  • Design and build production-grade data pipelines on Databricks (Google Cloud) using Databricks Workflows, Spark SQL, and Python. Focus on creating solutions that are fast to implement, cheap to maintain, and highly reliable.
  • Lead the adoption of Databricks best practices across the team: Delta Lake optimization, Photon query acceleration, cost governance, and performance tuning. Document and teach these practices so your teammates become independent.
  • Architect scalable lakehouse solutions that support both analytics and operational workloads, applying modern design patterns (medallion architecture, data mesh principles).
  • Mentor and upskill the team in Databricks: conduct code reviews, pair-programming sessions, and knowledge-sharing workshops. Your technical depth should elevate the entire group.

Requirements

We’re flexible! We’re happy to receive applications in English or German., * Databricks mastery: You have hands-on production experience with Databricks (1+ years), including:

  • Building and optimizing ETL/ELT pipelines with Apache Spark (PySpark or Scala), Lakeflow Connect, Lakeflow Pipelines
  • Delta Lake table design, optimization, and troubleshooting
  • Databricks Workflows for orchestration
  • Performance tuning
  • Cost optimization and monitoring
  • Backend data engineering: Several years of professional experience building data pipelines in distributed systems. Python and/or Scala proficiency is essential; SQL expertise is critical.
  • Modern tooling: Familiarity with Git-based version control, CI/CD principles, and testing frameworks for data code.
  • Cloud comfort: You have worked with Google Cloud Platform (or AWS/Azure) and understand cloud data warehouse/lakehouse architecture.
  • Analytical thinking: You can break down complex data problems, propose multiple solutions, and evaluate trade-offs (speed vs. cost vs. reliability).
  • Communication: You can explain technical concepts to non-technical stakeholders (business analysts, product owners) and translate their requirements into data engineering solutions. Fluent in Business English and German at an intermediate level minimum.

Benefits & conditions

  • Attractive salary package with many advantages such as childcare, meal allowance, job ticket, sports and leisure events
  • Flexible hybrid work concept and flexible working hours
  • Personal development through extensive training opportunities
  • A place in a dynamic and international team within EEX Group and Deutsche Börse Group
  • A long-term perspective in the constantly growing and evolving energy industry
  • Bespoke onboarding plan

About the company

to our World. Hello from ECC, the leading clearing house for energy and commodity products in Europe. As part of EEX Group, we have our roots in Leipzig and 24 offices worldwide. We provide security for our customers, by ensuring the physical and financial settlement of transactions for EEX Group and further partner exchanges. Why are we so successful? We are a team of individual experts that drive forward exciting projects while sharing experiences, celebrating success and creating memories, together. You have made it this far - together with us you can go further: Click on the “apply”-button and send us your application. You find additional job offers on our . We encourage women to apply and develop their careers with us.

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