Data Engineer for AI-Driven Analytics

Red Bull; Elsbethen; Vor Ort; EUR 24.000 - 29.000; Vollzeit

Zusammenfassung

Red Bull is seeking a data engineering specialist to design and operate data products and ELT pipelines across the organization. You will collaborate with data scientists, analysts and solution architects to implement scalable data solutions using Snowflake, Azure Data Factory, DBT, Dagster and Databricks while upholding governance and security standards.

You will work with business and IT stakeholders to deliver AI-ready analytics foundations, ensuring high data quality, metadata, and reliable

Qualifikationen

• University degree in IT or business administration with a data focus.
• Fluency in English; German is beneficial.
• At least three years with analytics tools: Snowflake, ADF, Databricks, BigQuery, Dagster, DBT.
• Experience with SQL and Python; knowledge of SAP is a plus.
• Ability to align data engineering with enterprise strategy, governance, security, and compliance.

Aufgaben

• Collaborate with data scientists, analysts, and architects to shape data solutions and ELT pipelines.
• Develop scalable data pipelines using Snowflake, ADF, DBT, Dagster and related platforms.
• Ensure data governance, security, and compliant operations across the data ecosystem.
• Partner with IT, business units and DevOps to maximize data availability and quality.

Kenntnisse

SQL

Python

Data governance

Stakeholder mgmt

Ausbildung

University degree in IT or business administration

Tools

Snowflake

Azure Data Factory

DBT

Dagster

Databricks

BigQuery

Jobbeschreibung

Red Bull is seeking a data engineering specialist to design and operate data products and ELT pipelines across the organization. You will collaborate with data scientists, analysts and solution architects to implement scalable data solutions using Snowflake, Azure Data Factory, DBT, Dagster and Databricks while upholding governance and security standards.

You will work with business and IT stakeholders to deliver AI-ready analytics foundations, ensuring high data quality, metadata, and reliable