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About the role
3+ years of experience as a Data Engineer working with large-scale data platforms and high-volume datasets
Strong expertise in data modeling, data warehousing concepts, and analytical data architecture design
Proven experience designing and developing complex ETL/ELT workflows following BI and data engineering best practices
Hands-on experience with BigQuery, including partitioning, clustering, query optimization, and cost management
Strong SQL skills with the ability to write and optimize complex analytical queries using Google SQL
Proficiency in Python and data processing libraries such as Pandas and PySpark
Experience working with ClickHouse, including architecture understanding, performance optimization, and migration approaches
Solid knowledge of Google Cloud Platform services, including Cloud Storage, Pub/Sub, DataForm, IAM, and service accounts
Experience with Git, CI/CD practices, automated deployments, and environment management for data workflows
Strong understanding of monitoring, logging, data validation, and production-grade data quality practices
Excellent analytical thinking, problem-solving skills, and ability to work independently in a fast-paced environment
Strong communication and collaboration skills with both technical and non-technical stakeholders
Understanding of product metrics, experimentation frameworks, and data-driven decision making
2+ years of previous Software Engineering experience
Experience optimizing storage and compute resources to improve infrastructure efficiency and reduce operational costs
Experience integrating data platforms with BI tools such as Tableau or Looker
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