Staff Data Engineer/Data Architect

Qualifications, Skills, Abilities and Educational Requirements

Required

•  Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field; equivalent practical experience will be considered in lieu of a degree.

•  5+ years of professional experience in data engineering, with hands-on ownership of production data pipelines and platform infrastructure.

•  Advanced proficiency in SQL and Python for data pipeline development, transformation, and automation.

•   Deep hands-on experience with Snowflake, including warehouse management, RBAC, query optimization, Tasks, Streams, Stages, and Snowpark.

•  Demonstrated experience designing and maintaining a Medallion or equivalent layered data architecture in a cloud data lake environment.

•  Experience integrating data from multiple heterogeneous source systems, including ERP platforms or transactional databases.

•  Experience building datasets for diverse consumers including BI/analytics, data science, ML/AI, and application teams.

•  Working knowledge of broad data engineering tooling including Apache Spark, dbt, Apache Airflow, or equivalent frameworks.

•   Experience implementing Data Governance practices including access control, data quality, lineage tracking, and metadata management.

•  Strong communication and stakeholder engagement skills, with the ability to translate technical concepts for non-technical audiences.

•   Proficiency with Git and CI/CD practices as applied to data engineering workflows.

Preferred

•    8+ years of data engineering experience with demonstrated technical leadership or staff-level platform ownership.

•   Experience in manufacturing, distribution, or industrial B2B environments.

•   Familiarity with Snowflake Cortex, Snowpark ML, or other ML-adjacent platform capabilities.

•   Experience operating in a multi-ERP source environment with complex entity resolution or data integration challenges.

•   Exposure to data mesh, data contract, or data product frameworks.

•    Experience with Tableau or similar BI platforms from a data provider/platform perspective.

•    Familiarity with private equity-backed company environments and the pace and expectations that come with them.