Expert Data Engineer

Ready to Build the Data Backbone Behind Next-Generation Technology?

If you’re the kind of Data Engineer who gets excited about Kafka, AWS, Python, Java, real-time streaming and solving complex data challenges, this could be your next big opportunity.

We’re looking for an Expert Data Engineer to join a high-performing global technology environment and play a key role in building secure, scalable and intelligent data integration solutions.

You won’t just be moving data from A to B. You’ll be designing the pipelines, platforms and integrations that make critical enterprise data available, trusted, discoverable and ready to be consumed in real time.

Requirements

• Hands-on experience with Kafka and event streaming platforms for real-time data movement.
  
• Proven experience with API integration patterns, webhooks and event/webhook ingestion.
  
• Strong proficiency in Python for data engineering, ingestion pipelines and automation.
  
• Strong proficiency in Java for stream processing or connector development.
  
• Solid competence with enterprise databases and query languages, including performance tuning and query optimization for OLTP/operational workloads.
  
• Experience with NoSQL/document stores such as Amazon DynamoDB, MongoDB.
  
• Experience in data modelling to design schemas and standardized data representations.
  
• Experience with schema registries and contract-first designs (Avro, Protobuf) to manage producer/consumer compatibility.
  
• Strong understanding and practice of data quality techniques and tooling to ensure trusted data.
  
• Knowledge of metadata management and cataloging to support discoverability and lineage.
  
• Familiarity with ETL/ELT patterns and best practices for performant, reliable data pipelines.
  
• Observability for streaming: experience with metrics, tracing and logging on AWS (CloudWatch, OpenTelemetry, Prometheus/Grafana).
  

• Awareness of frontend frameworks (e.g., Angular) to better understand downstream consumers.
  
• Experience operating container platforms and orchestration (Kubernetes/EKS) for scalable stream processing on AWS.
  
• Familiarity with enterprise systems like SAP and working with their integration interfaces.
  
• Experience with big data ecosystems (e.g., EMR, S3, Hadoop) and distributed storage/processing on AWS.
  
• Working knowledge of AWS analytics/data platform services (Glue, Athena, Kinesis, Redshift, Lake Formation, MSK).
  
• Knowledge of message delivery semantics, partitioning strategies and capacity planning for high-throughput pipelines on AWS.
  

• Extensive hands-on experience (typically 6+ years) in data engineering, integration or streaming roles with demonstrable production experience.
  
• Proven track record building and operating streaming platforms (Kafka/MSK) and API-based integrations, with strong Python and Java skills and experience with enterprise databases and query languages.
  
• Strong analytical thinking, curiosity about data, attention to detail, structured problem solving and ownership — able to drive topics to completion.
  
• Preferred certifications: Confluent Certified Developer for Apache Kafka, Microsoft streaming eventhubs, AWS Certified Data Engineer.
  

Benefits

• Cutting edge global IT system landscape and processes.
  
• Flexible working of 1960 hours in a 12-month period.
  
• High Work-Life balance.
  
• Remote / On-site work location flexibility.
  
• Highly motivating, energetic, and fast-paced working environment.
  
• Modern, state-of-the-art offices.
  
• Dynamic Global Team collaboration.
  
• Application of the Agile Working Model Methodology.