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

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

Senior Data Engineer

Key skills