Senior Data Engineer

Position Overview We are seeking a Senior Data Engineer to design, build, and maintain the data infrastructure that powers analytics, reporting, and data-driven decision making across the organization. In this role you will own the development of scalable, reliable data pipelines on a modern cloud data stack, partnering closely with analysts, data scientists, and business stakeholders to deliver clean, well-modeled, and trustworthy data. The ideal candidate is a hands-on engineer with deep expertise in Snowflake, SQL, and Python who can balance day-to-day delivery with longer-term architecture and data-quality goals. Key Responsibilities • Design, build, and maintain scalable ETL/ELT pipelines that ingest data from a variety of internal and external sources into the data platform. • Develop and optimize data models, schemas, and transformations in Snowflake to support analytics, reporting, and downstream applications. • Write efficient, well-tested SQL and Python to transform, validate, and orchestrate data workflows. • Tune queries, warehouse compute, and storage for performance and cost efficiency across the Snowflake environment. • Implement data quality, validation, and monitoring frameworks to ensure accuracy, completeness, and reliability of production data. • Partner with analysts, data scientists, and business stakeholders to translate requirements into robust, reusable data solutions. • Establish and uphold engineering best practices including version control, code review, testing, documentation, and CI/CD for data workflows. • Contribute to data governance, security, and access-control standards across the data platform. • Mentor junior engineers and provide technical guidance on data architecture and pipeline design. Required Qualifications • 7+ years of professional experience in data engineering or a closely related discipline. • Demonstrated hands-on expertise with Snowflake, including data modeling, performance tuning, and warehouse management. • Advanced SQL skills, including complex query development, optimization, and troubleshooting. • Strong programming proficiency in Python for data processing, automation, and pipeline development. • Proven experience designing and operating production-grade ETL/ELT pipelines at scale. • Solid understanding of data warehousing concepts, dimensional modeling, and data quality practices. • Strong problem-solving skills and the ability to work both independently and collaboratively in a team environment. • Must be a U.S. Citizen. Preferred / Nice to Have • Experience with dbt (data build tool) for transformation, modeling, and testing. • Familiarity with workflow orchestration tools (e.g., Airflow, Dagster, or Prefect). • Exposure to cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code practices. • Experience with CI/CD pipelines and version control workflows in a data engineering context. Applications from the following states are not accepted • California • Washington • Massachusetts • Washington • Oregon • Connecticut