(Senior) Data Engineer

Tasks – introduction

As a (Senior) Data Engineer, you will be responsible for developing and providing technical solutions to solve business issues through the use and support of (big) data. You develop and maintain ETLs of raw data from various source systems into analytics environments to support data discovery, analytical model development, and BI needs.We are looking for a data enthusiast who learns continuously, is a good listener, asks questions and is open to discussions. A colleague who likes to share their knowledge – all in all someone who is great to work with; a fast and delivery-focused (Senior) Data Engineer who can work in rapidly changing industries and tolerate ambiguity. We offer an opportunity to work with international clients, develop your knowledge and expertise, and build up a strong analytics company.

  • Translate business requirements into a data architecture and infrastructure
  • Design and build a robust data and analytics infrastructure which exposes data via relevant interfaces to clients and other teams
  • Guide and drive team members to deploy and test applications at scale
  • Support data scientists and BI developers on data and analytics initiatives and ensure optimal data delivery architecture is consistent throughout ongoing projects
  • Develop and execute the collection, storing, processing, modeling, and analyzing of multiple sources of data; design and develop scalable ETL routines
  • Consult with senior business leaders and data scientists to translate business goals into highly scalable data management systems
  • Work with cross-functional business, analytics, and IT teams to deliver maintainable, secure and multi-faceted use cases
  • Develop best practices for data engineering within DAIN Studios

What you contribute

  • 5+ years of professional data or backend engineering experience in building reliable and scalable data platforms
  • Bachelor/Master’s/PhD degree in computer science, computer science, or a related field
  • Solid SQL skills and database and data warehouse understanding, data modeling skills from dimensional modeling to Data Vault and Lakehouse architecture
  • Strong experience with Snowflake, Redshift, Aurora, MySQL, PostgreSQL, Azure SQL
  • Strong experience with distributed systems, eg. Athena / Presto, Databricks / Spark, Kafka
  • Proficient with the following languages: Python, Scala
  • Experience in CI/CD environments, DBT and orchestration tools such as Airflow
  • Experience with cloud providers: AWS, Azure, Google
  • Ability to work as an ML Engineer or develop into that direction preferred
  • (Nice to have) Experience with cloud migration projects
  • (Nice to have) Strong NoSQL, document database and unstructured datastore skills, Cosmos DB, MongoDB, Redis, DynamoDB
  • (Nice to have) REST API development skills
  • (Nice to have) German and/or Finnish language skills

What we offer you

  • Meaningful, high-impact projects with both domestic and international clients
  • Develop yourself as a data leader and contribute to the data communities in our studio cities
  • Independence and responsibility over your work
  • Develop your knowledge and career within a growing company
  • Devote time for cool internal projects in collaboration with your colleagues
  • Smart, fun and practical colleagues, with a wide range of hands-on expertise
  • Lean organization structure
  • A competitive salary to match your experience and competence
  • Annual personal learning & development budget and allocated time to ensure your knowledge and skills are continuously up to date
  • Healthy work-life balance: Wellbeing is the key for all learning and development.

Further information

📍You can choose to be based at any one of our office locations: Berlin, Helsinki, Munich, or Vienna. It is also possible to work remotely from within Germany, Finland, or Austria.

🚀 This job sounds interesting? Do apply here➡️

We looking forward to receiving your CV! 

Beratung | Ingenieurwesen | Technik und Technologie | IT und Informatik
Beratung & Recht | Elektrotechnik | Tech & Data
27 Tage
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