Data Engineer

Solid software engineering experience with the ability to design, implement, and deliver maintainable, high-quality code in Python
Hands-on experience with cloud computing and data processing technologies, including PySpark, Kubernetes, Kafka
Expertise in data modeling, relational databases (e.g., PostgreSQL), and object stores (e.g., AWS S3), cloud data platform (e.g. databricks), Data warehouse (e.g. Snowflake)
Proven expertise in making efficient and robust data pipelines, including optimizing their performance
Passion for data quality assurance, data monitoring
Expertise in end-to-end development processes, including unit, integration & functional testing, application tuning/profiling, and continuous integration
Extensive experience with agile methodologies, with a strong focus on delivery, lean thinking, and quick iterations
Ability to continuously develop yourself and learn from your peers
Ability to collaborate and mentor team members, while also sharing practical knowledge and trends

Take ownership of the end-to-end process, including architecture, design, development, deployment, and operations of data pipelines, applying DevOps practices, pair programming, and other cutting-edge methodologies
Be active, solution-oriented member of autonomous, cross-functional agile teams collaborating with Product Owners, Back-end Engineers, Front-end Engineers, Product Analysts, and Business Intelligence teams
Demonstrate an in-depth understanding of HelloFresh’s core product and architecture, and act as ambassador for software solutions offering support and mentorship to colleagues
Work with state-of-the-art technologies like AWS (EMR, Glue, s3, etc), Kafka, PySpark, Kubernetes, Airflow, Databricks, as well as our in-house Data Pipeline tools