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Red Bull

Manufactures and markets energy drinks

Data Engineer - Data & AI

Data EngineeringConfirmed live in the last 24 hours
Full-timeElsbethen, Austria€2.4k /moIn-person

About the Job

Requirements

  • A university degree in information technology or business administration with a focus on computer science, data science, or data engineering is required.
  • Fluency in English is required.
  • At least three years of experience with analytics tools such as Azure Data Factory, Snowflake, Databricks, BigQuery, Dagster, or dbt is required.
  • Experience with SQL and Python is required.
  • Architectural understanding of databases and extract, transform, and load/extract, load, and transform pipelines is required.
  • An enterprise mindset and the ability to align data-engineering solutions with broader business strategy, architecture, governance, security, compliance, and operational requirements are required.
  • Professional experience using AI coding assistants or AI-enabled data-platform tools is required.
  • Familiarity with data science and data lake platforms on modern hyperscalers such as Azure or AWS is required.

Responsibilities

  • Collaborate with data scientists, business analysts, and solution and analytics architects to shape data solutions and products.
  • Drive implementation, testing, and support of modern data pipelines using contemporary engineering practices.
  • Develop efficient approaches to data ingestion, preparation, integration, and operationalization to support data governance and compliance.
  • Develop dynamic extract, load, and transform pipelines using platforms and technologies such as Snowflake, Azure Data Factory, dbt, and Dagster.
  • Create scalable, secure, reusable, and maintainable data solutions aligned with enterprise architecture standards and best practices.
  • Apply artificial intelligence in support of business objectives while adhering to security, privacy, governance, and responsible artificial intelligence principles.
  • Work with AI engineers to design and productionize data foundations for AI-powered analytics, including data, features, embeddings, metadata, and evaluation datasets.
  • Work with Data Science teams, Data Cloud Architects, and business stakeholders to establish and improve governance frameworks and processes.
  • Build relationships across IT, Data, Sales, Operations, Marketing, Finance, and other business functions to foster organizational alignment and collaboration.
  • Partner with DevOps, MLOps, and Analytics Engineers to maximize data availability, reliability, and accuracy and continuously improve data quality.
  • Work with stakeholders to understand business requirements and use cases and translate them into data-driven solutions.
  • Drive continuous process improvement initiatives to improve efficiency and service delivery.
  • Create documentation and presentations to facilitate knowledge sharing, alignment, and communication across teams.

Desired Qualifications

  • German language skills are beneficial.
  • Knowledge of SAP BW, SAP HANA, SAP Analytics Cloud, and analytics front-end tools is beneficial.

About the Company

Red Bull

Manufactures and markets energy drinks

Red Bull makes and markets energy drinks. It focuses on a signature global beverage and uses a distinct marketing strategy to build the brand. How it works: the drink combines ingredients such as caffeine and sugars (originally based on Krating Daeng) and is carbonated for Western palates, distributed worldwide through large-scale marketing, sponsorships, and events to boost sales. How it differs: it remains privately held by the founding families, avoiding public funding, and relies on a marketing-heavy approach—extreme-sports sponsorships, high-profile events, and a strong brand identity—rather than conventional product features alone. What it aims to do: maintain leadership in the energy-drink category, grow globally through branding and partnerships, and continue expanding its product line and presence without going public.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
Salzburg, Austria
Founded
1984

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