Data Engineer (m/f/d)

Raisin; Frankfurt; Vor Ort; EUR 50.000 - 70.000; Vollzeit

Zusammenfassung

A leading company in the financial tech space seeks a Data Engineer to orchestrate scalable data pipelines and improve data processes. The role requires solid experience in Python, Airflow, and SQL, as well as a strong analytical background. You will collaborate with various teams to ensure high-quality data management while benefiting from a rich work culture and numerous employee perks.

Leistungen

Employee Development Budget of €2,000

Access to Babbel for language learning

Flexible working hours and home office

28 vacation days

Subsidized Urban Sports Club membership

Leasing a bike with tax benefits

Company pension scheme supported at 20%

Subsidized Deutschland Ticket for commuting

Qualifikationen

• Solid experience with Airflow and Python programming.
• Experience with cloud data warehouses like Snowflake is a plus.
• Strong analytical skills and problem-solving capabilities.

Aufgaben

• Work on and orchestrate scalable data pipelines.
• Collaborate with stakeholders to translate requirements into technical steps.
• Maintain CI/CD pipeline and promote knowledge sharing within the team.

Kenntnisse

Airflow

Python

SQL

dbt

Data Quality

Observability

Ausbildung

Bachelors in Mathematics, Computer Science or relevant quantitative fields

Tools

Snowflake

AWS

Docker

Jobbeschreibung

Work on and orchestrate scalable data pipelines to efficiently process and analyse large volumes of data, utilising Python, Snowflake, Airflow and dbt.

Collaborate with stakeholders to help translate their requirements into technical steps and coordinate the projects you drive with them.

Monitor and improve the health of our data pipelines.

Promote knowledge sharing within the team to foster collaboration and continuous learning.

Stay updated on emerging technologies and best practices in data engineering and bring new ideas to enhance the technical set-up.

Maintain our CI/CD pipeline on Harness.

Your Profile

• Solid experience with Airflow, Python programming and SQL / dbt.
• Experience with cloud data warehouses such as Snowflake is a plus.
• Knowledge of AWS services and Docker is a plus.
• Bachelors in Mathematics, Computer Science or other relevant quantitative fields.
• Strong analytical and quantitative approach to problems.
• Familiarity with Data Engineering best practices, including Data Quality and Observability.
• Comfortable working in a dynamic and changing environment, with a strong sense of responsibility.
• Eagerness to learn and grow through on-the-job learning.

Join our mission, join our team - and grow with us!

At Raisin, we care about each other and it is one of our top priorities to foster an open and caring environment in which everyone feels welcome and comfortable. Our culture is strongly driven by our ambitious team, which connects more than 40 different nationalities.

Our office is located in the trendy Kreuzberg district with a view of the Spree River, ideally connected to public transportation and surrounded by a variety of restaurants and shopping opportunities.

As part of our team, you will benefit from:

• Employee Development Budget of €2,000 and four full training days per year.
• Access to Babbel for continuous language learning.
• Snacks, daily fresh fruit, and drinks provided at the office.
• Flexible working hours, home office, and 28 vacation days.
• More than 50 sports options with Urban Sports Club: we subsidize your membership with over €20 per month.
• Leasing a bike through JobRad with tax benefits; Raisin covers your monthly insurance costs.
• A company pension scheme supported at 20%.
• Subsidized Deutschland Ticket for commuting.

Please note that if you are NOT a passport holder of the country for the vacancy, you might need a work permit. Check our Blog for more information.

Bank or payment details should not be provided when applying for a job. Eurojobs.com is not responsible for any external website content. All applications should be made via the 'Apply now' button.