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Data Engineer
hace 7 meses
**YOUR TALENT**:
- Bachelor's degree in computer science, engineering, or a related field. Equivalent work experience may be considered in lieu of a degree.
- Strong experience in designing, developing, and maintaining data pipelines and ETL processes on Google Cloud Platform (GCP).
- Proficiency in GCP data services, such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer.
- Solid understanding of data modeling concepts, database design principles, and SQL query optimization.
- Experience with data integration and orchestration tools, such as Apache Beam, Apache Airflow, or Talend.
- Knowledge of data warehousing concepts and experience with data warehousing solutions like BigQuery or Snowflake.
- Familiarity with streaming data processing and technologies like Apache Kafka or Google Cloud Dataflow.
- Understanding of data governance, security, and compliance standards in a cloud environment.
- Strong problem-solving skills and the ability to analyze complex data requirements and translate them into scalable and efficient data engineering solutions.
- Excellent communication and collaboration skills, with the ability to work effectively in a team-oriented, agile environment.
**YOUR MISSION**:
- Design, develop, and maintain scalable and performant data pipelines and ETL processes on Google Cloud Platform (GCP).
- Collaborate with stakeholders to understand data requirements and design data models, schemas, and architectures that meet business needs.
- Implement data integration solutions to ingest and transform data from various sources, including databases, APIs, and streaming platforms.
- Develop and maintain data warehouses and data lakes on GCP, ensuring data quality, integrity, and availability.
- Optimize data workflows and processing pipelines for performance and cost efficiency, leveraging GCP services like BigQuery, Dataflow, and Pub/Sub.
- Implement data governance and security measures, including access controls, encryption, and compliance standards, to protect sensitive data.
- Collaborate with data analysts and scientists to support their data exploration, analysis, and machine learning initiatives.
- Monitor and troubleshoot data pipelines and processes, ensuring the timely resolution of any issues or data anomalies.
- Document data engineering processes, standards, and best practices, and train team members on data engineering tools and technologies.
- Stay up-to-date with the latest data engineering trends, technologies, and best practices, and provide recommendations for continuous improvement.
PUMA provides equal opportunities for all job applicants, regardless of race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, or disability. Equality for all is one of the core principles at PUMA and we do not tolerate any form of harassment or discrimination.
PUMA supports over 16,100 employees across 120+ countries. The PUMA Group owns the brand PUMA, Cobra Golf and stichd, and is headquartered in Herzogenaurach, Germany.
