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Senior Data Product Engineer, Intelligent Platforms

Warszawa, Masovian Voivodeship, Poland

Live, first seen by us 66 days ago
Pay
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Work setting
Not stated
Employment
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What you’ll work on

Full posting
  • Design, 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

From the employer’s posting
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.
Education & alternatives
- 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.
Apply at HelloFresh

Posting record

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Status in our records
Live
First seen by us
Aug 31, 202666 days ago
Recorded sightings
164
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

HelloFresh is hiring

13 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
  • 15% of open jobs were reposted
Hiring record

See how this role fits your experience

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.

  • Python
  • SQL
  • AWS
  • Databricks
  • dbt
  • Airflow
Where the posting names them
- 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.

Your next step

Complete your application on careers.hellofresh.com. The employer’s form will show what is required.

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

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.

About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

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.

About the Team

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.

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

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. 

  • 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.
  • Build high-quality, well-modeled data pipelines for analytical purposes, enabling reliable reporting, experimentation analysis, and self-serve insight at scale across HelloFresh.
  • 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.
  • 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.
  • Contribute to a collaborative and knowledge-sharing environment, providing technical guidance and coaching to team members and stakeholders.
  • Work beyond your specialization when the problem demands it. Your specialization is your anchor, not your boundary.
  • Operate what you build. You instrument, monitor, and improve your systems in production. Shipping is the beginning of the learning cycle, not the end.

What You'll Bring: The Ingredients

  • 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.
  • 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.
  • Expertise in leveraging Generative AI tools (eg. Claude, Copilot) to support development, experimentation, and documentation.
  • Exceptional communication capabilities to interact effectively with product managers, product analysts and business stakeholders.
  • You take full ownership. You have a bias to ship. You finish the last twenty percent. 
  • You have product sense and are opinionated about what should be built and why, and you can back that opinion with data and user evidence.

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.

What we offer: The Toppings

  • Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
  • Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
  • Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
  • End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
  • Access to workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

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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