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