Senior Data Engineer
Summary
Design and build scalable data pipelines and models using Python, DBT, Airflow, PySpark, Databricks, and AWS infrastructure, while ensuring data quality, governance, and compliance.
Responsibilities:
- Design, build, and optimize scalable pipelines for data, supporting insight into the the Data Foundation ecosystem
- Design and implement data models using industry best practices that capture a complete ecosystem view of internal customer experiences, while ensuring accuracy, scalability,and long-term usability
- Architect and implement robust, maintainable, and high-performance data solutions
- Automate workflows to reduce manual intervention and enhance data processing efficiency, including automation for content, growth, and pubsports areas of coverage
- Optimize query performance and resolve pipeline bottlenecks to improve data accessibility
- Evaluate and adopt new tools, frameworks, and methodologies to advance data engineering capabilities
- Support cost optimization by ensuring scalable and efficient data solutions
- Ensure data quality, governance, and compliance with regulatory standards (e.g., GDPR, CCPA)
- Contribute to engineering discipline by shaping infrastructure, craft standards, tooling, and organizational best practices
Kogo poszukujemy?
Required Qualifications:
- Minimum of 5 years commercial work experience in data engineering or a related field
- Bachelor’s or higher degree in Computer Science, Software Engineering, or a related field
- Proficiency inPython, essential for data processing and analysis tasks
- Hands-on experience withDBT andAirflow
- Commercial experience usingPySparkandDatabricks
- Proficiency inAWScloud infrastructure (AWS)
- Effective communication and teamwork skills
Nice to Have:
- Experience withML OperationsandGenAIpipelines and infrastructure
- Experience in thegaming industry, particularly with online multiplayer games
- Experience working with cross-discipline organizations that build data products
- Proficient in large-scale data manipulation across various data types
- Demonstrated ability to troubleshoot and optimize complex ETL pipelines
- Proven experience mentoring and guiding other engineers