Data Engineer

Job Title: Data Engineer Company: Siemens Job Category: Data Science Roles & Responsibilities: At Siemens, we are scaling the Siemens Data Mesh to power the next generation of industrial AI, smart infrastructure, and digital excellence. Within Data Domain Operations, trusted, high-performance, and real-time data is the foundation of operational excellence. We are looking for a hands-on Data Engineer who is passionate about data in motion – transforming Kafka event streams provisioned by our central data ingestion platform into governed, consumer-ready data products using platforms such as Flink. This person will champion a "shift left" mentality, embedding quality and automation at the source rather than downstream. Move the world with your passion for data and impactful, AI-ready technologies. Rethink how we integrate and process data, and steer the organization toward a future where event-driven insights power every decision. Be bold when others would have given up. In short, play a key role in building the real-time data foundation of Siemens! * As a Data Engineer within Data Domain Operations, you will design, build, and automate streaming data products that transform Kafka event streams – already provisioned by our central data ingestion platform – into trusted, consumer-grade data assets. Operating at the heart of our real-time architecture, you will implement robust pipelines for data in motion using platforms such as Flink, working closely with our data architects to bridge operational source systems and the analytical platforms that depend on them. * Build Streaming Data Products: Design, build, and operate real-time and near-real-time data products sourced from Kafka event streams, using stream-processing engines such as Flink. * Engineer Event-Driven Pipelines: Develop and automate robust, resilient pipelines for data in motion, covering transformation, enrichment, and delivery of streaming events into our operational and analytical platforms. * Champion Shift-Left Data Engineering: Embed data quality checks, schema validation, testing, and monitoring directly into the pipeline development lifecycle, catching issues at the source rather than downstream. * Treat Data as a Product: Design streaming data products with clear data contracts, documentation, and SLAs, in line with data-as-a-product principles across the Siemens Data Mesh. * Bridge Operational & Analytical Systems: Collaborate with domain architects and analytics engineers to connect Kafka-based event streams with downstream warehouses (such as Snowflake) and reporting layers, supporting real-time operational decision-making. Automate & Operate with DataOps Rigor: Apply CI/CD, automated testing, containerization, and infrastructure-as-code practices to streaming pipelines, ensuring reliable, repeatable deployments. * Monitor & Resolve Proactively: Monitor streaming pipeline health, identify and resolve data issues proactively, and contribute to the domain’s data governance and quality framework. * Collaborate & Mentor: Work with cross-functional teams to translate business requirements into technical solutions, and share streaming and event-driven engineering best practices with peers across the domain. This role is based out in Pune or Bangalore and gives you the chance to work with international teams that shape the future of Siemens’ Operations and Data Analytics landscape. Work Location: KA, India Availability: Full time

* Education: University degree in Computer Science, Data Science, or a related technical field. * Professional Experience: 1 year of experience as a data engineer, with a strong focus on data integration, ETL/ELT, and building production data pipelines. * Streaming & Event-Driven Processing: Hands-on experience with Kafka (or Confluent Cloud) and stream-processing engines such as Flink or Camel, building event-driven data products that operate on data in motion. * Stream Processing & Schema Management: Experience with stateful stream-processing concepts (windowing, joins, exactly-once semantics) and schema registries (e.g., Confluent Schema Registry) for managing evolving event schemas. * Cloud & Warehouse Exposure: Hands-on experience with cloud-based data platforms (AWS, Azure, or GCP) and modern cloud warehouses such as Snowflake. * Programming & Engineering: Proficiency in Python and expert-level SQL skills, basic working knowledge of Java, along with data engineering best practices such as data versioning, automated testing, and CI/CD for data pipelines. * DataOps Mindset: Familiarity with shift-left data quality practices, monitoring, and observability for streaming pipelines. * Ways of Working: Experience with agile software development methodologies, and excellent problem-solving and analytical skills, with a proven ability to translate complex business requirements into technical solutions. * Languages: Fluency in English (verbal and written); knowledge of German, Portuguese, or other languages is a plus. We’re Siemens. A collection of over 312,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we encourage applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and imagination and help us shape tomorrow. Key Skills: Data Science, Python, SQL Salary: Not disclosed