Data Engineer

• Manage assignment, workflow, and oversight processes to ensure quality, consistency, and timeliness of data engineering deliverables
• Create and maintain standards for data design, modeling, and deployment in Snowflake
• Provide direction and training regarding foundational applications used in the development lifecycle
• Assess new data ingestion patterns to improve efficiency and timeliness of data availability
• Define data delivery strategy and monitor data release schedules
• Provide guidance to data analysts on best practices for leveraging and querying new data assets
• Interpret business needs and rapidly implement effective technical solutions supporting consistent enterprise data delivery
• Create and maintain ETL source-to-target mapping documents, data playbooks, and data flow inventory documents
• Provide technical guidance and best practices for design, modeling, and data presentation/implementation
• Ensure the team’s skillsets support future success

Manager, Data Engineering

• Build, refactor, and maintain pipeline components of cloud-based data products
• Own ingestion, storage, cleansing, profiling, transformation, and presentation of data products
• Analyze large and complex datasets for quality, accuracy, anomalies, and performance
• Own pre-UAT testing for every change using the standard ABC framework
• Consult with analysts and stakeholders on data requests, enhancements, recommendations, quality, and awareness
• Assess integration restrictions and options, and recommend load strategy, storage targets, data access layer model, and solution architecture
• Participate in modeling star-schema data marts, denormalized performant layers, presentation layers, and Data Vault or other immutable storage
• Organize source code using a versioning framework
• Create and maintain reference architecture diagrams and engineering documentation
• Triage emergent data concerns and coordinate with stakeholders through resolution