Data Engineer

Siemens is seeking a passionate and skilled Data Engineer to join our dynamic Data Domain Operations team. In this pivotal role, you will contribute to scaling the Siemens Data Mesh, empowering the next generation of industrial AI, smart infrastructure, and digital excellence. We are looking for an individual who is eager to transform Kafka event streams into governed, consumer-ready data products using cutting-edge platforms like Flink, championing a 'shift-left' mentality for quality and automation.

Key Responsibilities

• Design, build, and operate real-time and near-real-time streaming data products from Kafka event streams using stream-processing engines such as Flink.
• Develop and automate robust, resilient pipelines for data in motion, covering transformation, enrichment, and delivery of streaming events to operational and analytical platforms.
• Embed data quality checks, schema validation, testing, and monitoring directly into the pipeline development lifecycle.
• Design streaming data products with clear data contracts, documentation, and SLAs, aligning with data-as-a-product principles across the Siemens Data Mesh.
• Collaborate with domain architects and analytics engineers to connect Kafka-based event streams with downstream data warehouses like Snowflake and reporting layers.
• Apply CI/CD, automated testing, containerization, and infrastructure-as-code practices to streaming pipelines, ensuring reliable and repeatable deployments.
• Proactively monitor streaming pipeline health, identify and resolve data issues, and contribute to data governance and quality frameworks.
• Work with cross-functional teams to translate business requirements into technical solutions and share event-driven engineering best practices.

Requirements

• University degree in Computer Science, Data Science, or a related technical field.
• 3+ years of experience as a data engineer with a strong focus on data integration, ETL/ELT, and building production data pipelines.
• Hands-on experience with Kafka (or Confluent Cloud) and stream-processing engines like Flink or Apache Camel.
• Experience with stateful stream-processing concepts (windowing, joins, exactly-once semantics) and schema registries (e.g., Confluent Schema Registry).
• Hands-on experience with cloud-based data platforms (AWS, Azure, or GCP) and modern cloud warehouses such as Snowflake.
• Proficiency in Python and expert-level SQL skills, with basic working knowledge of Java.
• Familiarity with DataOps mindset, shift-left data quality practices, monitoring, and observability for streaming pipelines.
• Experience with agile software development methodologies and excellent problem-solving skills.

What We Offer

• The opportunity to work with international teams shaping the future of Siemens’ Operations and Data Analytics landscape.
• A vibrant international team dedicated to innovation and digital excellence.
• A commitment to equitable opportunities and a diverse, inclusive workplace.
• Chances to work with cutting-edge technologies like industrial AI and smart infrastructure.
• Mentorship and growth opportunities within a globally recognized company.