Junior Data Engineer - Spark

Our engineering group is split into roughly 60 product teams, each owning its services end to end, with on-call shared across time zones. Headquartered in Berlin since 2000, the company now sells in 40 countries and supports customers in 11 languages. We keep recurring meetings to Tuesdays and Thursdays where we can.

The position

The Data Engineering team moves data from about 30 source systems into Snowflake. You'll own ingestion, modelling and data quality checks. Krüger Data needs someone who writes solid SQL and Python and treats pipelines like production software. Remote, open to candidates across Germany. Communication happens mostly in Slack and short video calls.

Responsibilities

• Process large datasets with Spark on Databricks or EMR
• Model data in dbt using staging, intermediate and mart layers
• Write data quality tests with dbt or Great Expectations and alert on failures
• Respond to pipeline failures and backfill data when needed
• Design table layouts and partitioning for Parquet, Delta Lake or Iceberg
• Maintain CI for data code and review pull requests
• Document datasets and lineage in a catalogue such as DataHub or Atlan
• Ingest data from APIs, SaaS tools and databases with Fivetran, Airbyte or custom Python

Qualifications

• 1+ years of data engineering, or backend work with data at volume
• Working knowledge of AWS, GCP or Azure data services
• Strong Python for data processing
• Familiarity with Git, CI/CD and testing practices for data code

Preferred

• Reverse ETL tools like Hightouch or Census
• Background in finance or marketing data
• Terraform for data infrastructure

Rate: €54,000 - €65,000 per year

What you get

• Company pension scheme
• 30 days of annual leave
• Christmas bonus
• Meal allowance
• Flexible working hours
• Up to 3 days of home office per week

Please submit your CV in English.

Start: Immediately.

Demo job created on 11jobs for testing and demonstrations. It is not an actual opening at Krüger Data.