Senior Data Engineer - Enterprise Integration & Data Platform (f/m/d)

Description

The company builds rockets and launch services that carry small and medium satellites and constellations into low Earth orbit, aiming to make space access cheaper, greener and easier to scale.

The company is growing fast and is privately funded by major technology investors. Its team works on new approaches to a traditional industry.

This is a senior, hands-on role in building the foundation of the enterprise data platform. You will connect business applications, engineering systems and operational data, working with SAP, Siemens Teamcenter and other enterprise systems to build pipelines, integration services and a modern data lake.

You will have real technical ownership, shaping the data architecture, setting engineering standards and building the infrastructure other teams use to reach data across the organisation.

If you like solving hard integration problems, working with mixed data sources and pairing solid engineering with a practical approach, get in touch.

Responsibilities

• Design, build and maintain scalable pipelines that link enterprise applications, engineering systems and operational data sources.
• Help set up the architecture of a central enterprise data lake or lakehouse.
• Build ingestion, transformation and processing workflows for batch and event-driven use cases, working on your own.
• Design storage and processing layers for structured, semi-structured and unstructured data.
• Define data models, transformation patterns and organisation standards that keep systems consistent.
• Add monitoring, error handling, logging and automatic recovery to keep pipelines reliable.
• Assess data technologies, frameworks and architectural patterns and recommend the suitable ones.
• Build and maintain integrations with SAP ERP, Siemens Teamcenter PLM and other internal platforms.
• Use APIs, databases, file interfaces and messaging systems to exchange data reliably.
• Extract, transform and harmonise data from varied systems while keeping it intact and traceable.
• Create reusable connectors, integration components and data services for future integrations.
• Work with application owners to understand their data models, interfaces and business processes.
• Keep systems synchronised and interoperable while respecting which system owns each dataset.
• Build pipelines and curated datasets for internal applications, analytics, dashboards and operational reporting.
• Create reusable data models and services so teams can reach information spanning several systems.
• Set up data quality checks, validation rules, lineage tracking and metadata management.
• Help build one consistent data foundation across engineering, manufacturing, supply chain, finance and business operations.
• Enable business intelligence, advanced analytics, AI and ML, and process automation.
• Improve processing speed, storage efficiency and pipeline reliability as data volumes and needs grow.
• Set best practices for version control, automated testing, CI/CD, documentation and infrastructure automation.
• Work closely with software engineers building internal applications and platforms.
• Turn data needs from engineering, manufacturing and business stakeholders into technical solutions.
• Apply security, access control and data governance principles to enterprise data.
• Use modern tools, including AI-assisted coding, to speed up implementation, testing and troubleshooting.
• Shape the long-term enterprise data strategy and architecture.

Requirements

• 5+ years of professional experience in data engineering, software engineering or enterprise data integration.
• Strong Python and SQL skills for production-grade data pipelines and services.
• Extensive experience integrating relational databases, APIs and enterprise applications.
• Strong knowledge of relational databases such as PostgreSQL, MySQL, SQL Server or comparable systems.
• Experience building ETL and ELT pipelines, including transformation, validation and orchestration.
• Experience with data lake, data warehouse or lakehouse architectures.
• Good grasp of data modelling, data quality and metadata management.
• Experience with workflow orchestration, scheduling, monitoring and automated data processing.
• Familiarity with REST APIs, JSON, XML and common enterprise data exchange patterns.
• Experience with Git, CI/CD, automated testing and modern software engineering practices.
• Proven ability to design, implement and run reliable data solutions independently.
• Strong analytical skills and the ability to understand complex enterprise data models.
• Excellent English communication skills and the ability to work across technical and business teams.
• Experience integrating enterprise platforms such as SAP ERP and PLM systems like Siemens Teamcenter.
• Familiarity with BOMs, part revisions, product configurations and material master data.
• Familiarity with Delta Lake or Apache Iceberg.
• Experience with change data capture, event streaming or message-based integration.
• Familiarity with Docker, Kubernetes, infrastructure as code and cloud-native development.
• Experience with enterprise data security, access management and governance frameworks.
• Experience supporting analytics, machine learning or AI-ready data infrastructure.
• Experience in aerospace, automotive, manufacturing or other engineering-intensive industries.
• Practical experience with AI-assisted engineering tools such as GitHub Copilot, Claude Code or OpenAI Codex.
• You build, not only design: you write code, develop pipelines, troubleshoot integrations and deliver working solutions.
• You think beyond single pipelines and value reusable architecture, common data models and long-term maintainability.
• You collaborate with application owners, software engineers and business stakeholders to solve real problems.
• You evaluate new data technologies and development approaches, choosing them by practical value.

Benefits

• Virtual company share programme that lets employees share in company success.
• 30 days of vacation.
• Company pension plan with a 20% employer contribution after the probation period.
• Subsidised lunch every day.
• Public transport ticket with the Deutschlandticket fully financed.
• Rental workwear with a laundry service.
• Sponsored sports club memberships through EGYM Wellpass.
• Individual learning budget available after the probation period.
• Childcare allowance for children who are not yet of school age.
• Further perks and benefits are available once you join the team.