As a senior Data Engineer at WorkMotion, you will be at the heart of a modern, scalable, and cloud-native data platform. You'll help drive the development and maintenance of our end-to-end data infrastructure, supporting everything from ingestion to reporting. If you thrive in a fast-paced environment, enjoy building robust data pipelines, and want to work with a highly motivated international team, this is the role for you.
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What You’ll Do
Design, build, and maintain scalable ETL pipelines using Apache Airflow and AWS Glue (Spark)
Work with a range of data sources including Salesforce, NetSuite, PostgreSQL, and MongoDB
Develop and optimize PySpark jobs for large-scale data transformation and analytics
Manage data lake infrastructure using Delta Lake on S3 with Athena as the query layer
Ensure data quality, performance, and reliability through monitoring, testing, and documentation
Collaborate with analytics, product, and engineering teams to define data requirements
Contribute to CI/CD workflows with GitHub and deployment automation
Participate in architectural discussions and advocate for best practices in data engineering
3-5 years of professional experience in Data Engineering or Software Development with a focus on data
Strong knowledge of Python and SQL; and PySpark.
Hands-on experience with AWS services (Glue, S3, Athena, EC2)
Experience with Apache Airflow, preferably in a Dockerized/cloud-native environment
Familiarity with Delta Lake or similar data lake frameworks
Proficiency with source control (GitHub) and CI/CD workflows
Strong understanding of data modeling, ETL best practices, and data pipeline performance optimization
Why Join Us
Work with a cutting-edge, cloud-native data infrastructure
Join an international team with flexible remote work opportunities across Europe
Collaborate in a modern agile environment with a focus on high-quality engineering
Personal development budget and career growth opportunities
Competitive compensation and benefits tailored to the European market
