Data Engineer

Responsibility

The engineer (M/V/X)

• supports the engineering of event-driven data products, data integrations and API’s

• continuously improved the way of working by adding monitoring & automation,

• coaching & reviewing the work of the application engineers, design and document blueprints, building POC’s etc.

• part of the time he also does hands-on work on software design & the engineering of event stream processing for more complex features, including integrations with cloud services, API design etc. and provides coaching & guidance to meet the engineering standards.
  

Skills & experience

Hands-on, senior experience with (“the basics”):

• Java, Spring Boot & it’s modules

• Git, CI/CD, configuration-as-code principles and tooling

• HTTP, REST-style API’s with JSON

• Micro-services architecture

• Messaging with JMS / AMQP (RabbitMQ)

• SQL & RDBMS

• Docker, Maven

• AWS services (S3, DynamoDB, RDS, …) & IAM

• Kubernetes (EKS)

• Apache Kafka (MSK) & Kafka Connect

• Event stream processing with Kafka Streams

• Avro, Confluent Schema Registry

• Kustomize, Helm

• Ansible, Terraform

• Prometheus & Grafana

• Technical writing

• Platform thinking, evolutionary architecture

Experience with, notions of or profound interest in (“nice to have”):

• gRPC, GraphQL

• ELK stack

• GitOps, ArgoCd/FluxCD

• EAI patterns, WSO2

• AWS Lambda

• Akka

• Python

• Airflow, Dbt

• Data engineering & DataOps