[TECH] Senior Data Engineer [FOUNDATIONS]

at  Alumni Network Job Board

At HelloFresh, we want to change the way people eat forever by offering our customers high-quality food and recipes for different meal occasions. Over the past 10 years, we’ve seen this mission spread around the world and beyond our wildest dreams. Now, we are a global food solutions group and the world’s leading meal kit company, active in 18 countries across 3 continents. So, how did we do it? Our weekly boxes full of exciting recipes and fresh ingredients have blossomed into a community of customers looking for delicious, healthy and sustainable options. The HelloFresh Group now includes our core brand, HelloFresh, as well as: Green Chef, EveryPlate, Chefs Plate, Factor_ and Youfoodz.

THE ROLE

As a Data Platform Engineer at HelloFresh, you will be part of a team that builds a data platform that processes data in batch and real-time with a focus on scalability, data quality, cost efficiency, and resilience.
Our team develops a low-code, config-based, unified platform product that simplifies and streamlines building data products. That platform is leveraged by internal users to increase their efficiency and reduce the time it takes to turn data into insights.
Interacting with software engineers, data engineers, analysts, and product owners is part of our daily work, so communication skills are vital. We are looking for strong problem-solvers who can apply their engineering skills to a wide range of platforms and environments.
Our tech stack: Python, AWS cloud, S3, Airflow, Apache Spark, EMR, Databricks, Snowflake, dbt
Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

WHAT YOU’LL DO

• Build tools and services for other data engineers, data scientists, data analysts, and non-data professionals
• Build reusable and convenient technology that enables teams to ingest, store, transform, and serve their own data products
• Collaborate closely with domain data teams to support them in adopting our services and tools
• Collaborate closely with data architecture and modeling teams to implement best practices on a wide scale
• Advocate for data quality, data governance, and data product thinking