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About
Design and build ETL/ELT data pipelines to ingest, process, and transform large datasets from multiple sources. Implement best practices for performance tuning, partitioning, and clustering to optimize data queries and reduce costs. Establish and enforce data quality standards, data governance frameworks, and security policies for data storage and access. Develop and optimize data models and schemas to support analytics, reporting, and machine learning requirements. Collaborate with data scientists and analysts to design data solutions that integrate with BI tools and machine learning models. Create comprehensive documentation for data pipelines, workflows, and processes. Share best practices and mentor junior data engineers. Requirements:
5+ years of applicable work experience Proficiency in Python, specifically with ETL pipelines. Strong proficiency in SQL and experience in developing complex queries. Familiarity with pySpark, DBT, or other similar frameworks. Experience deploying data pipelines in a cloud environment (Azure, AWS, GCP). Understanding of data warehousing concepts, dimensional modeling, and building data marts. Excellent communication and interpersonal skills, with the ability to collaborate effectively with data scientists, analysts, and product owners. Benefits:
medical, dental, and vision coverage paid time off retirement savings options wellness programs other resources, based on eligibility
Languages
- English
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