Lounge by Zalando is the fastest growing part of Zalando, now turning over billions of euros each year. That said, there is so much untapped potential with respect to personalization and recommendation.

You will be the senior data engineer, leading others to build a large scale recommender system. We are the largest online fashion retailer in Europe, as such we need an exceptional engineer who can write Machine Learning pipelines in Spark at a global scale. You will own everything from batch / stream preprocessing, model training, and model / feature distribution to the real time recommender system.

You will have full autonomy to direct architectural decisions, and help to implement state of the art ML recommender algorithms. There are very few roles which offer this unique synthesis of scale and ML complexity.

INCLUDED BY DESIGN

At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit.

We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.

do.BETTER - our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy

Our employee resource groups: https://corporate.zalando.com/en/our-impact/our-employee-resource-groups

WHAT WE'D LOVE YOU TO DO (AND LOVE DOING)

• Provide critical data infrastructures like large-scale ETL processes, DWHs, stream processing and batch processing pipelines, large-scale high-throughput/low-latency data stores, data governance mechanisms and so on

• Improve the pace of innovation by building and improving ML infrastructures such as training/evaluation frameworks, experimentation frameworks

• Collaborate with brilliant Product Managers, Data Scientists, Engineers and Analysts across Zalando to create positive customer impact together

• Help define our team's objective. Continuously improve the self-organization of the team.

• Mentor and grow junior and mid-level members of the team

WE'D LOVE TO MEET YOU IF

• You have 6+ years of experience in large-scale data engineering using open source technologies

• You have solid experience with large-scale batch processing and/or stream processing (eg Spark, Hadoop, Flink, Storm, Apache Beam, Kafka, Airflow, Oozie etc.)

• You are passionate about topics like data democratization, data governance, privacy, data quality assurance

• You are proficient in at least one of: Python, Scala, Java

• You have Excellent knowledge of distributed databases, especially high-throughput/low-latency data stores like DynamoDB, Cassandra, Aerospike, Redis etc. is a strong plus

OUR OFFER

Zalando provides a range of benefits, here's an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.

• Employee shares program

• 40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners

• Two paid volunteering days a year

• In a hybrid working model with 60% remote per week, actual practice is up to each team to best support their collaboration

• Work from abroad for up to 30 working days a year

• 27 days of vacation a year to start

• Relocation assistance available (subject to prior agreement)

• Family services, including counseling and support

• Health and wellbeing options (including Gympass)

• Mental health support and coaching are available

• Drive your development through our training platform and biannual peer-to-peer review

Learn all about Zalando and our values ​​here: https://jobs.zalando.com/en/?gh_src=22377bdd1us

fernanda.porto@zalando.de

Please note that all applications must be completed using the online form - we do not accept applications via email.