Senior Data Engineer

ELT pipelines using AWS Infrastructure, Azure Infrastructure, Apache Airflow, Snowflake, and dbt.

Oversee the design, development, and optimization of a unified data platform across cloud environments.

Manage the development and maintenance of data models and schema designs to support efficient data storage and retrieval.

Manage schema evolution processes from product data sources to Snowflake.

Optimize data processing workflows for performance, scalability, and reliability.

Act as a subject matter expert for internal stakeholders and clients, addressing technical inquiries and providing strategic guidance.

Implement and maintain robust data governance, security, and compliance frameworks.

Ensure data quality, security, and integrity through effective validation, cleansing, testing, and monitoring technique.

4+ years of experience in data engineering.

Proven expertise in AWS, Azure, Snowflake, dbt, and Python.

Strong background in data warehouse architecture, data modeling, and performance tuning.

Proficiency in SQL, dbt, and Python for data transformation and orchestration.

Experience with cloud-native architecture, DevOps practices, and CI/CD pipelines in Azure, AWS, and GitHub.

Excellent communication and collaboration skills with the ability to influence technical direction and strategy.

Works on problems of diverse scope where analysis requires identifying and evaluating factors from limited information. Devises solutions by adapting and applying existing approaches, exercising judgment within established practices. Impact is primarily at the team and project level.

Builds productive working relationships and influences senior partners outside own immediate team on technical matters. Adapts communication style for diverse audiences to explain approaches and gain support for recommendations.

Fully remote role within the United States

Periodic travel (approximately 5%) for team meetings, customer visits, and industry events

Operates in a fast-paced, growth-oriented, PE-backed SaaS environment

Requires cross-functional collaboration across Data Engineering teams

Ability to manage multiple concurrent and shifting priorities

Success in this role requires the ability to balance synchronous collaboration with thoughtful asynchronous execution in a remote-first environment.