Senior Data Engineer

5+ years of experience in data engineering, focusing on data warehousing, ETL/ELT pipelines, and data modeling. Proven experience in designing and implementing data warehouses using the Kimball dimensional modeling methodology. Strong proficiency in Python for data processing and automation. Hands-on experience with dbt for data transformation and testing. Experience with Amazon Web Services (AWS) for data storage, processing, and analytics services. Experience with data products designed for external customers. Experience with Customer Data Platforms (CDP) is a bonus. Familiarity with Infrastructure as Code (IaC) principles and tools (e.g., Terraform, CloudFormation) is a bonus. Ability to participate in an on-call rotation.

Apply advanced Data Engineering principles to design and implement data loading and aggregation frameworks. Gather and process raw, structured, semi-structured, and unstructured data using batch and real-time frameworks. Implement and optimize data solutions in enterprise data warehouses and big data repositories using systems like Snowflake or Databricks. Design and develop robust data solutions using Kimball data modeling techniques. Develop, test, and maintain data pipelines using Python and dbt. Work closely with product managers and stakeholders to deliver external-facing data products. Understand and enforce appropriate data master management techniques. Lead the implementation of tools for automating data quality issue identification. Partner with the analytics organization to design viable data solutions. Provide subject matter expertise and guidance for internal and external customers. Play a lead role in planning, providing advice, mentoring engineers, and monitoring emerging technologies. Recommend improvements to processes, technology, and interfaces.