DataChef is building a greenfield, AWS-based data mesh platform for one of the largest global distribution companies. They are looking for a pragmatic, experienced data engineer for a consultant role, designing and building large-scale stream processing systems with Spark and Kafka.
Responsibilities
- ▹Design and build a scalable data mesh platform on AWS
- ▹Build stream processing backend using Spark (Scala/Python) and Kafka
- ▹Ingest new data sources via REST APIs and file sharing
- ▹Handle ever-changing schemas and ensure resilient pipelines
- ▹Act as a consultant to clients and the team
Requirements
- ▹Solid Scala and/or Python skills, deep language internals knowledge
- ▹2+ years hands-on experience with AWS (Lambda, EMR, Glue, Lake Formation)
- ▹Experience with pub-sub/async systems (Kafka, SQS, Kinesis, RabbitMQ)
- ▹Understanding of algorithm complexity and data structures
- ▹3+ years using Linux/macOS, Docker and git in collaborative workflows
- ▹Excellent communication skills for a consultant role
Nice to have
- ▹Experience with ZIO
- ▹5+ years in live, high-availability production environments
- ▹Familiarity with Great Expectations or Deequ
- ▹Writing clean, testable, maintainable code
Soft skills
Excellent communication, simplifying concepts for othersSelf-driven, finishes what they startFast learner, agile mindset
About the company
DataChef is a data engineering consultancy that also contributes to open-source projects such as ZIO and Great Expectations.
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