Data Engineer
Thalgau, Austria
Red Bull
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The Red Bull Athlete Performance Center serves as a dynamic accelerator for Red Bull athletes, propelling them towards unparalleled excellence in their respective sports. Leveraging advanced technology, cutting-edge analytics, and insights gleaned from a diverse array of sporting disciplines, we unlock the individual potential of each athlete.
As the APC undergoes rapid expansion, both in physical infrastructure and strategic sport disciplines such as soccer, ice hockey, and Formula 1, our commitment to enhancing data infrastructure, engineering, and analytics capabilities remains unwavering. This investment underpins our mission to provide unparalleled support and resources to athletes and teams striving for greatness.
In this fast-paced environment, the Data Engineer plays a pivotal role as the APC's Data Engineering lead. They are responsible for supporting heavy data-users across various departments within the APC, ensuring a reliable data pipeline that fuels decision-making and innovation. Additionally, the Data Engineer collaborates closely with high-end sports data analysts and data scientists from the global data team, spanning APC, Red Bull Soccer, and Red Bull team sports/clubs. Together, we harness the power of data to drive performance, unlock insights, and propel our athletes towards victory on the world stage.
Job Description
Technical responsibility over data pipelines and data platforms
Design, create, maintain and scale batch and stream data pipelines to ingest data from various data sources into cloud-based data storages
Transform and model data in close alignment with data analysts and make data available to data consumers such as Data Scientists
Utilize latest technologies to work with structured and unstructured data in a highly integrated landscape
Analyze and discuss business processes, data flows and functional/technical requirements
Evaluate, propose, and select proper application solutions and vendors in alignment with HQ IT
Steer external vendors and partners
Monitor and manage corresponding IT budget
Manage and contribute to analytics projects
Lead and support analytics projects according to the IT Project Management methodology
Collaborate with Data Science and with business to refine data requirements
Translate the data requirements into ETL/ELT pipelines and data models
Implement or monitor the implementation of data pipelines while ensuring a high data quality
Train Data Scientists to integrate and use the data they need for their own use cases
Manage communication between business, IT partners and HQ IT
Service Ownership for assigned IT data & analytics applications
Act as Service Owner for selected data & analytics applications
Define service strategy and roadmap in alignment with involved stakeholders
Supervise service operations and support
Manage vendors, service level agreements and contracts
Care for proper service definition and documentation
Cooperate with central service or platform owners
Qualifications
Higher education in Computer Science, Information Systems, Mathematics, Physics, or related quantitative field or equivalent work experience
3 or more years of work experience as data engineer or software engineer with strong hands-on data skills
Practical experience working with ETL/ELT pipelines, cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and other cloud-native technologies, ideally in AWS or Azure
Minimum of 3 years' experience in project management
General skills/knowledge:
Inter-personal contact
Diplomacy
Conceptual working
Organize, prioritize and coordinate multiple tasks
Flexibility
Analytical thinking
Problem solving
Hands-on mentality
Performance and result orientation
Positive attitude and a strong commitment to delivering high-quality work
Team player
Languages: fluent in German and English
IT related skills/knowledge:
Very good skills in SQL, Python or another general-purpose language like R, C++ or Java
Very good skills working with APIs, databases, data modelling and data transformation (ideally with dbt)
Solid understanding of the professional software development process following the DevOps methodology including Git, Branching Workflows, CI/CD, Containers and automated testing
Architectural knowledge related to Cloud, databases and ETL/ELT
IT Project Management
Bonus:
Experience with dbt and/or workflow management tools like Airflow or Prefect
Experience with Infrastructure-as-Code tools like Terraform
Experience with streaming technologies, such as Spark Structured Streaming, Kafka Streams or Apache Flink
Familiarity with best practices for data architecture, data modelling, and/or data engineering
Additional Information
Due to legal reasons we are obliged to disclose the minimum salary according to the collective agreement for this position. However, our attractive compensation package is based on market-oriented salaries and is therefore significantly above the stated minimum salary.
As an employer, we value diversity and support people in developing their potential and strengths, realizing their ideas and seizing opportunities. The job advertisement is aimed at all people equally, regardless of age, skin colour, religion, gender, sexual orientation or origin.
As an employer, we value diversity and support people in developing their potential and strengths, realizing their ideas and seizing opportunities. We believe passionately that employing a diverse workforce is central to our success. We welcome applications from all members of society irrespective of age, skin colour, religion, gender, sexual orientation or origin.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs Architecture AWS Azure BigQuery CI/CD Computer Science Data pipelines Data quality dbt DevOps ELT Engineering ETL Flink Git Java Kafka Mathematics Physics Pipelines Python R Redshift Snowflake Spark SQL Streaming Terraform Testing Unstructured data
Perks/benefits: Career development
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