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Salary
$103k – $125k per year
Location
Remote/Hybrid (Leverkusen, Germany)
Employment
Full-Time
Overview
Company
Impact
Profile match
Covestro AG is a global manufacturer of high-performance polymer materials and industrial chemical precursors. Headquartered in Leverkusen, Germany - having originally spun off from Bayer in 2015 - the company operates dozens of production sites worldwide. Its primary operations span two major business segments: Performance Materials (producing bulk polyurethanes and polycarbonates) and Solutions & Specialties (delivering custom engineering plastics, specialty films, coatings, adhesives, and elastomers).

We are Covestro. We are curious. We are courageous. We are colorful. We refine chemical material solutions with game-changing products. Let us empower you to push boundaries. Join us and our 18.000 colleagues now and together we will make the world a brighter place.

Do you want to do more than just manage data - and create real value for science? At Covestro, data engineering meets cutting-edge research. As a Data Engineer (m/f/d) in our Digital R&D team, you'll be part of a growing, international team driving the digitalization of chemical research and development - from lab automation and data science to high-performance computing and quantum computing.

We're currently building our Data Office: a new team with deep expertise in R&D processes and the data they generate. This is where you come in.

In addition to our wide range of benefits, a full-time position offers an attractive starting salary between€89,400/year and €108,500/year plus a variable component. The starting salary is based on your qualifications and professional experience.

What you'll be doing:

  • You take ownership of designing and implementing data integration and data management solutions - with a focus on research & development, product management, and sustainability
  • Project requirements are analyzed independently, identifying relevant data sources and appropriate tools for data provisioning
  • You develop and operate data pipelines for integration, transformation, and quality assurance of production data - with scalability and maintainability in mind
  • Data models are designed purposefully for various analytical use cases, and you maintain a company-wide data mesh catalog
  • You build and operate CI/CD pipelines for automated testing, deployments, and infrastructure provisioning
  • In close collaboration with cloud architects and platform teams, you actively shape the automation, monitoring, and observability of data solutions
  • You contribute actively to data governance initiatives - covering metadata management, data lineage, and access control

What you bring to the table :

  • You hold a degree in mathematics, computer science, natural sciences, or engineering (STEM) - or a comparable qualification with relevant hands-on experience
  • Additionally, you have solid professional experience in data engineering, ideally in a scientific or industrial environment
  • Python is your primary programming language, and you apply it confidently in data pipeline contexts
  • SQL, analytical query engines (e.g. AWS Athena), and distributed data processing with PySpark are part of your technical toolkit
  • You have hands-on experience with AWS Cloud Services - in particular S3, Glue, Athena, Lambda, ECS, Step Functions, Lake Formation, and CDK
  • dbt (Data Build Tool) or comparable transformation frameworks are familiar to you, as is Infrastructure as Code (AWS CDK, CloudFormation)
  • CI/CD workflows with GitHub Actions and Git-based development processes are second nature to you - as is containerization with Docker, ECR, and ECS Fargate
  • Strong English skills, both written and spoken, round off your profile

Nice to have, but not a must :

  • Experience with single-node data processing frameworks such as Polars or DuckDB
  • Knowledge of Lakehouse architectures (Apache Iceberg, Delta Lake) and data mesh concepts
  • Experience with data visualization (Streamlit, SAP Analytics Cloud)
  • Familiarity with data governance tools such as OpenMetadata, OpenLineage, or DataZone
  • Experience with monitoring and observability (Grafana, CloudWatch)
  • Knowledge of workflow orchestration tools (Apache Airflow, AWS Step Functions)
  • Familiarity with modern Python tooling and package management (uv, ruff, AWS CodeArtifact)

This position is generally intended as a full-time role. Prefer part-time? Feel free to apply and simply indicate your preferred percentage.

For initial questions, please contact Chris Rziha ([email protected]). Please do not use this email address to send your application or CV. To apply, please click the "Apply" button. Applications submitted by email will not be considered.

#LI-Hybrid

Perfection? Not required!

The requirements are not met 100%, but you are still interested in the position? Are you curious, courageous and colorful as we are? No problem!

We'll tackle this together - as a team! With proper onboarding and tailored development opportunities.

Apply now!

We look forward to receive your application! Become #1ofUs!

Anyone who wants to contribute to a better world with Covestro can also expect a lot.

We want you to feel at home at Covestro. To feel you’re treated fairly and transparently. That means financial security, a healthy work-life balance and generous benefits.

Specifically, it means for us: flexible working hours, the compatibility of family and work, active health promotion and the ability to convert part of your salary into long-term or retirement savings. And that's not all.

Sounds exciting? Find out more about Covestro and our benefits here:

https://www.career.covestro.de/de/about-covestro/covestro-as-an-employer/employee-benefits

Contact Us

www.covestro.com

Covestro welcomes applications from all individuals, regardless of racial or ethnic origin, skin color, nationality, religion, philosophy, gender, age, physical characteristics, marital status, disability, appearance, sexual orientation and sexual identity. We are committed to treating all applicants fairly and avoiding discrimination.

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