Senior Data/ML Engineer (all genders)

Eurowings Digital GmbH
Köln, Germany
20 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Köln, Germany

Tech stack

Artificial Intelligence
Data analysis
Azure
Cloud Computing
Cloud Engineering
Continuous Integration
Information Engineering
Data Infrastructure
ETL
Distributed Computing Environment
Fault Tolerance
Github
Python
Machine Learning
Uptime
Raw Data
Scala
SQL Databases
Data Streaming
Unstructured Data
Azure
Spark
Reliability of Systems
Production Code
Kafka
Machine Learning Operations
Terraform
Data Pipelines
Databricks
Programming Languages

Job description

We are looking for a versatile, senior Data / ML Engineer to join us. You will sit at the critical intersection of Data Engineering and Machine Learning, serving as the bridge between raw data infrastructure and production-ready AI models.

This role requires a pragmatic engineering mindset. You will be responsible for architecting robust data pipelines, designing scalable transformation logic, and building the MLOps infrastructure required to deploy, monitor, and scale machine learning workflows in production.

What you will do

  • Data Infrastructure & Pipelines: Design, build, and maintain scalable, fault-tolerant data pipelines (ETL/ELT) to ingest and process large-scale structured and unstructured data using Spark and cloud-native architectures
  • ML Systems & MLOps: Collaborate closely with Data Scientists to transition experimental models into clean, production-ready code and robust pipelines
  • Analytics Engineering: Implement advanced data modeling and transformation logic to ensure high-fidelity inputs for both downstream models and business analytics
  • Operational Excellence: Build continuous integration and deployment (CI/CD) pipelines for data and ML workflows, ensuring system reliability, data quality, and uptime

Technical Stack:

  • Languages & Frameworks: Scala, Python, SQL, Spark (with experience using Spark in production environments)
  • Cloud & Infra: Azure Cloud Platform, Databricks, Kafka
  • CI/CD & IaC: Azure DevOps / GitHub, Terraform

Requirements

Do you have experience in Terraform?, * Experience: 7+ years of experience in data engineering, ideally with hands-on exposure to analytics engineering practices (e.g., data modeling, transformation logic)

  • Data Science Partnership: Proven experience working closely with data scientists or driving data science projects with a highly pragmatic, production-focused mindset
  • Core Engineering: Deep understanding of data pipeline orchestration, distributed processing, and building resilient, testable ETL/ELT systems
  • Data Modeling: Solid grasp of data modeling concepts, especially in the context of analytics and reporting (conceptual, logical, and physical models)
  • Streaming: Familiarity with streaming data frameworks (Kafka, Event Hubs, or similar), * Excellent Communication: Ability to explain complex technical concepts to both technical and non-technical stakeholders
  • Collaboration Mindset: Strong ability to work effectively with cross-functional teams including data science, engineering, and business units
  • Stakeholder Management: Skilled in balancing immediate business needs with long-term technical feasibility
  • Quality Focus: High attention to detail with a strong focus on data quality, accuracy, and reliability
  • Execution: A self-starter with strong organizational skills and the ability to drive initiatives from concept to completion

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