Data Engineer

With constant innovation, cutting-edge technology, and fast-paced development, we’re looking for talented professionals to join our Information Technology team to help us continue delivering an unparalleled customer experience. The Data Engineering department oversees the standardization, management, and adoption of services that support key technology initiatives, while also collaborating on cloud architecture, automation, data pipeline development, and data modeling to support business intelligence and data science goals. This team plays a critical role in leveraging data assets to drive actionable insights and innovation across the organization. 

The Data Engineer is responsible for building and maintaining data pipelines that move and transform data from Stuller’s systems into its cloud data warehouse. Working with senior team members, this role follows established data modeling patterns to support business intelligence, analytics, and data science.  This role provides the opportunity to develop end-to-end data solutions using a modern data engineering technology stack. The Data Engineer will write and test dbt models, gain exposure to the semantic layer and analytics engineering practices, and develop reliable solutions through regular design and code reviews.

Key Responsibilities

• Build, test, and maintain ETL/ELT pipelines that move data from ingestion to consumption using established tools and patterns, including Airflow.
• Write and test dbt models under the guidance of senior team members.
• Write performant SQL while following established schema conventions in the Snowflake data warehouse.
• Transform and integrate data from multiple sources into models that support reporting and analytics.
• Support semantic layer development and analytics engineering practices under senior team guidance.
• Monitor data workflows, troubleshoot issues, and help identify and resolve data quality concerns.
• Follow established data security, governance, testing, and deployment practices.
• Develop awareness of warehouse compute costs and avoid wasteful query patterns.
• Collaborate with analytics and data science teams to understand and support their data needs.
• Complete well-defined tasks reliably, participate in regular design and code reviews, incorporate feedback, and escalate blockers appropriately.

Minimum Qualifications

• Bachelor’s degree in Computer Science or a related technical field, or equivalent relevant experience.
• Foundational understanding of SQL and relational database concepts.
• Exposure to ETL/ELT concepts and pipeline tools, including Airflow.
• Basic familiarity with dbt or a similar transformation framework, or a strong aptitude to learn.
• Understanding of core data warehouse concepts, including schemas, roles, and warehouses.
• Awareness of the cost implications of compute-intensive queries.
• Strong problem-solving skills and attention to quality and detail.
• Strong communication skills within a team setting.
• Ability to manage assigned work, follow established guidelines, incorporate feedback through regular reviews, and escalate blockers appropriately.
• Demonstrated curiosity, reliability, integrity, and commitment to continuous learning.

Preferred Qualifications

• Hands-on experience with Snowflake, AWS, or Python.
• Experience with data modeling in analytics environments.
• Familiarity with semantic layers or analytics engineering practices.
• Experience with Agile development practices.