Principal Data Engineer

• Design and develop data pipeline to move data from disparate sources for consolidation and analysis
• Partner with Data Scientists, Engineers, and Product Managers to understand data needs and opportunities
• Establish industry leading design patterns around data ingestion, lifecycle management, governance, and and consumption
• Work with other leaders and team members to create technology roadmap, address technical debt, and put together an execution plan
• Design and develop data schemas and implementation strategies to provide fast analytics turnaround on petabytes of data
• Quickly come up to speed on existing pipeline and analytics infrastructure, identify areas of improvement, and adopt industry best-practices for data processing, movement, and management
• Develop robust monitoring infrastructure and strategy to return rapid insights into various stages of data handling
• Evangelize design and processes for data handling, CI/CD, security, extensibility, maintainability, etc.

Important Note: Although we list out what we generally look for, we are very likely missing other attributes and skills that you have that could make you a great fit, but are not currently listed. Research has shown this especially applies to women and other marginalized groups, who tend to apply if they check 100% of every box, versus men who apply if they hit roughly 60%. The point we’re getting at, it doesn’t hurt to take a chance and apply!

• BS/MS in Computer Science or Engineering, or equivalent experience
• 7+ years of progressive industry experience in design and implementation of data focused cloud software
• Hands-on experience in designing and maintaining data schema lifecycle
• Experience with designing and implementing real-time and batch processing pipelines
• Strong understanding of in-memory processing and data formats (Parquet, JSON, etc.)
• Experience with automated analysis of data quality and validation
• Hands-on experience with data transformation, SQL queries, and optimization
• Strong programming skills in Python
• Hands-on Experience with multiple data technologies, including Snowflake, Redshift, Airflow, Stitch, Spark, Kafka, S3, dbt, etc.