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Data Engineer (m/f/d) - Personalization - Remote Europe

IntermediateFull timeRemote
English - Advanced
Data QualitymlData AccessOptimization TechniquesHiveData EngineerData ModelingHADOOPsparkContinuous IntegrationEngineeringSQLAWSDevelopment



Who we are

Lykon is an innovative company working in the area of Digital Health Care & Self Tracking. We are defining the Healthcare Industry by developing digital applications to become your personalized healthy lifestyle companion. Our vision is to empower people to live a healthy life.

At Lykon, we give personalized recommendations based on blood results to help you develop healthy habits. At our Berlin office you’ll find a dynamic and fast-paced work environment, and people who are highly motivated to create products our customers will fall in love with.

About the opportunity

The Personalization team helps customers to better understand their health and achieve their goals. From Behavioural Change to Discover your next test, we’re behind some of Lykon’s most-loved features. We built them by understanding the world of health and nutrition better than anyone else.

We are looking for a mobile engineer to join our team and help us deliver the best personalized experience to our customers on our mobile app. You will play a vital role in how people interact with our products, and features where accessibility, testability, and simplicity are always part of the conversation.


  • Build batch and real-time data pipelines with data processing frameworks like Scio, Storm or Spark and AWS.
  • Deliver scalable, testable, maintainable, and high-quality code.
  • Demonstrate standard methodologies in continuous integration and delivery.
  • Help drive optimization, testing and tooling to improve data quality.
  • Work in multi-functional agile teams to continuously experiment, iterate and deliver on new product objectives.
  • Facilitate and drive collaboration with engineers, product managers and partners to seek exciting and results-oriented user-centric data problems.
  • Share knowledge, promote standard methodologies, making your team the best version of itself through mentorship and constructive accountability.


  • You know how to work with high volume heterogeneous data, preferably with distributed systems such as Hadoop, and Redshift. Ideally you have also built innovative solutions that address current limitations of these technologies.
  • You have used one or more high-level processing frameworks such as Beam, Dataflow, Crunch, Scalding, Storm, Spark, or something we didn’t list- but not just Pig/Hive/BigQuery/other SQL-like abstractions.
  • You have proven understanding about data modeling, data access, and data storage, caching, replication, and optimization techniques.
  • You have experience with user-centric feature engineering for ML systems.
  • You have worked in a cloud-native (AWS preferred) development and production environment where all CI/CD take place.
  • You care about agile software processes, data development, reliability, and responsible experimentation.
  • You understand the value of collaboration within teams.
  • You are comfortable with asynchronous communication, being able to work independently while always sharing context with your team members.
  • You give and receive open, direct, and timely feedback.


We are a remote distributed team. You can work anywhere within the European Timezone (UTC 0/+3).

  • Great internal corporate health program and employee discounts.
  • Competitive compensation and a personal education budget.
  • Flexible working hours. If you prefer early starts or late finishes your team will support you.
  • Annual learning and development budget for conferences, books, courses, you choose.
  • A diverse and vibrant remote international environment.
  • You will have a direct impact on our products and will have the opportunity to empower people to live a healthy life.

We foster a unique company culture by championing our vision, self-empowerment, direct communication, and mutual support. If this sounds like something you’d like to be a part of, let’s talk!