Senior Data Engineer (Enterprise Integration & Data Platform)

Location: Parsdorf, Bavaria, Germany

Company

hirify.global develops sustainable launch solutions for small and medium-sized satellites and constellations in Low Earth Orbit, building rockets and infrastructure for more affordable and scalable access to space.

What you will do

• Design, develop, and maintain scalable data pipelines connecting enterprise applications, engineering systems, and operational data sources.
• Help establish a centralized enterprise data lake or lakehouse, including data storage, processing layers, models, transformation patterns, and organization standards.
• Build batch and event-driven ingestion, transformation, processing, monitoring, error handling, logging, and automated recovery workflows.
• Develop integrations with SAP ERP, Siemens Teamcenter PLM, and other platforms using APIs, databases, file interfaces, messaging systems, and enterprise integration technologies.
• Create reusable connectors, integration components, data services, curated datasets, quality checks, lineage tracking, and metadata management practices.
• Establish data engineering practices covering version control, automated testing, CI/CD, documentation, infrastructure automation, security, access control, and data governance while collaborating with technical and business stakeholders.

Requirements

• 5+ years of professional experience in data engineering, software engineering, or enterprise data integration.
• Strong Python and SQL skills, including production-quality data pipelines and services.
• Extensive experience integrating heterogeneous data sources, including relational databases, APIs, and enterprise applications.
• Strong knowledge of relational databases such as PostgreSQL, MySQL, SQL Server, or comparable systems.
• Experience with ETL/ELT pipelines, data transformation, validation, orchestration, scheduling, monitoring, and automated processing.
• Experience with modern data platform architectures, including data lakes, data warehouses, or lakehouses, plus data modeling, data quality, and metadata management.
• Familiarity with REST APIs, JSON, XML, and common enterprise data exchange patterns.
• Experience with Git, CI/CD, automated testing, and modern software engineering practices.
• Ability to independently design, implement, and operate reliable data solutions; strong analytical skills; and the ability to understand complex enterprise data models.
• Excellent communication skills in English and the ability to collaborate across technical and business teams.

Nice to have

• Experience integrating SAP ERP and PLM systems such as Siemens Teamcenter.
• Familiarity with engineering and manufacturing data structures, including Bills of Materials, part revisions, product configurations, and material master data.
• Familiarity with lakehouse technologies and open table formats such as Delta Lake or Apache Iceberg.
• Experience with change data capture, event streaming, or message-based integration patterns.
• Familiarity with Docker, Kubernetes, infrastructure as code, and cloud-native development.
• Experience with enterprise data security, access management, governance frameworks, 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.

Culture & Benefits

• Employee participation through a virtual company share program.
• 30 days of vacation and a company pension plan with a 20% employer contribution after the probation period.
• Subsidised lunches, a fully financed Deutschlandticket, and rental workwear with laundry service.
• Sponsored sports club membership and an individual learning budget after the probation period.
• Childcare allowance for non-school-age children.
• Fast-growing, collaborative environment focused on space innovation, sustainable launch solutions, and practical engineering.