About The Role

As a Lead Data Warehouse Engineer you will work on developing a modern data pipeline integrating data from a variety of data sources in order to bring the data into the analytics platform using highly scalable and extensible pipeline technologies.   You’ll be a thought leader to help contribute to our best practices of modeling standards and pipeline standards, and ensure the models and pipelines you build and other build adhere to these standards.

What You'll Do

• Determine the best practices of what happens with the warehouse, gaining consensus with other engineers and publish data modeling standards and expectations, and ETL methodologies.
• Build curated data models which will be used by data consumers to address business questions today and in the future, ensuring the data model is extensible and flexible.
• Research and analyze the nature of the data to understand nuances and patterns of the data.
• Collaborate with BI Engineers and various other groups to ensure they get the data they need in an easy to use manner.
• Code review other engineers' code including data models and pipelines for adherence to standards and best practices.
• Be the go-to person for helping with performance issues, both query and pipeline performance.
• Propose solutions on how to handle security issues surrounding access, PII, and business-sensitive data and work to implement them.
• Be a team player in contributing your thoughts and ideas to the overall goals of the team.

What We Look For

• Bachelor's degree in Computer Science or other technical field or equivalent work experience
• 3+ years of developing in the cloud ; 7+ years of data warehouse implementations
• Experience using cloud analytics platforms which could include Google Big Query, AWS Redshift or Snowflake and standard relational databases such as Postgres, MySQL or other transactional databases
• Excellent SQL experience with working through complex queries.
• Great understanding of warehouse data modeling methodologies such as Kimball Dimension models, and its practical implementation.
• 3+ years of relevant experience working with data load and transformation tools which might include Airflow, Lambda’s, DBT, Presto, AWS Glue, or similar platforms.
• Exposure in developing batch systems and real time streaming platforms.
• Solid Python or Java skills; with UNIX shell scripting being helpful
• Experience with continuous integration, testing, and deployment using tools such as Git and Jenkins; nice to have some Docker experience as well.
• Expertise in the design, creation, management, and business use of large datasets.
• A willingness to being in an on-call rotation
• Strong multitasking skills with the ability to balance competing priorities
• Ability to work in a fast-paced environment where continuous innovation is desired, and ambiguity is the norm
• Experience with agile or other rapid application development methods
• Ability to coach / mentor other team members as appropriate