Data Engineer

Your Role in the Team

At Statista, we're all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions.

As a Data Engineer on our Statista R Data Platform, you'll own data ingestion and platform reliability end-to-end: designing and operating scalable batch pipelines, hardening orchestration, ensure data quality, security, and cost efficiency.

You'll partner closely with Data Analysts, Software Developers and Data Scientists to deliver well-governed datasets tailored for the teams' specific need and maturity to make high-quality data accessible and trustworthy for analysis.

• Develop and optimize ELTs/ ETLs to integrate new data sources and enhance data management in the data lake and other systems.
• Develop reliable data orchestration workflows to ensure and support the ranking creation process of Statista R's analyst teams.
• Drive cross-functional collaboration with engineering, data science, and analysis teams to deliver documented, reproducible datasets that power rankings, KPIs and business decisions.
• Monitor and optimize data infrastructure to ensure high availability, performance, and security.

Our Offer

In addition to our great team, culture, and our shared goal of empowering people with data, there are many other things that make Statista a great place to work!

Join us and benefit from:

• Work from abroad up to 30 calendar days a year.
• Hybrid work and flex-time.
• International team and social events.
• Subsidized urban mobility and access to fitness and wellness options.
• Free access to Langdock and all its amazing functionalities.
• Career & training opportunities.
• Attractive locations and modern offices.
• Mental health support with OpenUp.

Technologies and Skills

• Amazon Athena
• Amazon S3
• Snowflake
• RDS
• SQL
• Git
• AWS
• Airflow
• Python
• Docker
• Amazon ECS

Our Expectations of You:

Qualifications

• Bachelor's or master's in computer science, Data Science, Engineering, or related field.
• Comfortable in developing ELT/ETL processes and data automation processes using Python and SQL.
• Proficiency in workflow orchestration, containerization and version control tools (e.g. Apache Airflow, Docker or git).
• Good understanding of data modelling and architecture, with a strong interest in best practices.
• Knowledge in dlt, dbt, Snowflake, infrastructure as code and software development best practices is a plus.

Experience

• 2+ years in data engineering building production pipelines and platforms; including a sustained period within one organization seeing a product through build launch iteration.
• Hands-on experience in cloud services and infrastructure (e.g. AWS: S3, Glue, Athena, ECS, RDS).

Benefits

• Betr. Altersvorsorge
• Team Events
• Gesundheitsförderung
• Home Office