Time since we first saw it
Day 66
Similar jobs usually come down between day 6 and day 70.
At HelloFresh, jobs usually come down by about day 53.
From 4,444 similar postings that came down, and 32 of HelloFresh’s. Coming down is not always a hire.
Warszawa, Masovian Voivodeship, Poland
Live, first seen by us 66 days agoDesign, build, and operate behavioral data and experimentation platform components
Build well-modeled data pipelines for reporting and experiment analysis
Own reliability and governance of platform components: schema, events, lineage, quality checks
Extend the semantic layer with domain teams that define metrics
Use Generative AI to add capabilities to the data platform
Design, build, and operate the platform components behind our behavioral data and experimentation infrastructure
Build high-quality, well-modeled data pipelines for analytical purposes
Own reliability and scalability of data platform components - schema governance, event standards, lineage, and data quality checks.
Extend and evolve our semantic layer, partnering with domain teams who federate metric definitions on top of it.
Leverage Generative AI to improve and add new capabilities to the data platform.
- Hands-on experience working with AI tooling (e.g., Claude Code, Cursor, Copilot) beyond casual experimentation. You use AI agents every day. You have a practical sense of how the context you provide to AI tools shapes output quality, and how to set boundaries on AI-generated work. - Proven track record of scientific or engineering work (Bachelor's, Master's, or PhD) in computer science, software engineering or related field. - 5+ years of work experience as a Data Engineer, including delivery of production data. 2+ years on data platform systems - eg. semantic layers, catalogs, schema/governance systems.
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Day 66
Similar jobs usually come down between day 6 and day 70.
At HelloFresh, jobs usually come down by about day 53.
From 4,444 similar postings that came down, and 32 of HelloFresh’s. Coming down is not always a hire.
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 5+ years of work experience as a Data Engineer, including delivery of production data. 2+ years on data platform systems - eg. semantic layers, catalogs, schema/governance systems. - Fluency in Python and dbt, and building large scale high quality data pipelines on a modern cloud stack. - Technical proficiency in SQL for retrieving, manipulating, and analyzing large datasets.
- Fluency in Python and dbt, and building large scale high quality data pipelines on a modern cloud stack. - Technical proficiency in SQL for retrieving, manipulating, and analyzing large datasets. - Experience with software development practices and tools such as Git, CI/CD, and AWS.
- Extend and evolve our semantic layer, partnering with domain teams who federate metric definitions on top of it. - Work with state-of-the-art technologies like Snowplow, Statsig, AWS, Airflow, Databricks Unity Catalog and Metric Views. - Collaborate with product managers, product analysts and data scientists to create reusable, well-governed data products and to ensure the platform supports fast, trustworthy experiment readouts.
- Technical proficiency in SQL for retrieving, manipulating, and analyzing large datasets. - Experience with software development practices and tools such as Git, CI/CD, and AWS. - Expertise in leveraging Generative AI tools (eg. Claude, Copilot) to support development, experimentation, and documentation.
About the Role: What's in the Box As our Senior Data Engineer, you'll play a crucial part in extending and operating the platform behind our behavioral data - from event & experiment pipelines to Databricks Unity Catalog and semantic layer integrations, to the systems and standards that let other teams validate hypotheses on top of our platform. This isn't a pure data pipeline-building role: you'll reason about system design, schema governance and develop a technology platform as much as data engineering. Your deep understanding of behavioral tracking and data platform systems enables you to identify pain points across Behavioral Data Collection and Experimentation, and to design solutions that improve how we work at scale. What You'll Do: The Recipe
- Become an integral part of a high-impact data platform team, covering behavioral and experimentation data products. - Design, build, and operate the platform components behind our behavioral data and experimentation infrastructure (Snowplow, Statsig, Databricks, Unity Catalog). - Leverage Generative AI to improve and add new capabilities to the data platform.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.
Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.
HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.
Behavioral Data & Experimentation Platform is a cross-functional team with end-to-end ownership of digital tracking across all markets globally at HelloFresh - from infrastructure all the way to curated data products and the hypotheses validation mechanisms (eg. AB testing, quasi-experiments). The squad brings together software engineers, data engineers, and data scientists to build the tracking, event, and statistical infrastructure that every tech team relies on to drive product decisions. Our work enables customer experience improvements and business growth.
As our Senior Data Engineer, you'll play a crucial part in extending and operating the platform behind our behavioral data - from event & experiment pipelines to Databricks Unity Catalog and semantic layer integrations, to the systems and standards that let other teams validate hypotheses on top of our platform. This isn't a pure data pipeline-building role: you'll reason about system design, schema governance and develop a technology platform as much as data engineering. Your deep understanding of behavioral tracking and data platform systems enables you to identify pain points across Behavioral Data Collection and Experimentation, and to design solutions that improve how we work at scale.
At HelloFresh we are moving away from a model where software developers just execute tickets toward one where product engineers are trusted to own customer problems. A Product Engineer takes a problem, forms a point of view, validates it with customers and data, and ships it using AI as a force multiplier.
Above all, we are looking for people who will make HelloFresh better. 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.
Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you. We aim to review your profile and respond within 5 business days.
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Warszawa, Masovian Voivodeship, Poland
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