Lead Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the complete architecture, implementation, and development of the Snowflake-based data lakehouse spanning bronze, silver, and gold layers.

• Define and direct the pipeline strategy.

• Design and create ELT processes that ingest and transform data from SQL Server, Workday, and cloud-based services utilizing dbt Core.

• Spearhead the transition from legacy data logic and infrastructure.

• Establish and uphold data modeling standards, schema conventions, and best practices for medallion architecture.

• Manage Snowflake security, role-based access controls, and ensure data governance complies with FERPA and institutional policy.

• Automate and orchestrate data workflows using Python and Prefect in conjunction with Azure-based services.

• Collaborate with data consumers to guarantee data is accurate, timely, and usable.

• Monitor and troubleshoot Snowflake environments, enhance query performance, and resolve pipeline issues.

• Document system architecture, data flows, and technical configurations.

• Assess Snowflake, dbt, and ecosystem tools to enhance scalability, automation, and maintainability.

• Lead, mentor, and develop a high-performing data engineering team.

• Perform additional duties as assigned.

• Report to the Chief Information Officer (CIO) under general supervision.

• Collaborate with software engineers, institutional research, Power BI developers, and the Office of Innovation and Enhancement.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.

• At least 3 years of practical experience managing and administering a Snowflake environment, including aspects of configuration, optimization, and security.

• Experience in delivering a comprehensive data lakehouse end-to-end from inception, encompassing 5+ source systems, enterprise-scale data volumes, architectural decisions, schema design, medallion architecture, data governance framework, and migration from legacy systems.

• Proficiency in Snowflake environments, including data loading, Snowflake SQL, Streams, Tasks, transformation, and security management.

• Hands-on experience with dbt Core or dbt Cloud, covering model development, testing, documentation, and production deployment.

• Strong experience in developing ELT solutions that integrate cloud-based and on-premises data sources.

• Experience with Fivetran or a similar managed EL platform is highly preferred.

• Solid SQL skills with practical experience in Microsoft SQL Server.

• Experience using Python for data transformation, orchestration, and automation.

• Experience with a workflow orchestration platform is required; Prefect is strongly preferred.

• Familiarity with Workday reporting data or similar ERP/SaaS data platforms is preferred.

• Working knowledge of cloud environments, particularly Azure.

• Experience in supporting business intelligence solutions using tools like Power BI.

• Understanding of data governance and security frameworks, including FERPA compliance.

• Excellent communication skills with the ability to articulate architectural priorities, manage stakeholder expectations, and challenge requests that conflict with platform strategy or engineering best practices.

• Must be authorized to work for any employer in the United States; employment visa sponsorship is not available.

🏝️ Benefits

• Student-focused work environment.

• Opportunity to contribute to intellectual and spiritual growth, leadership, and service.

• Opportunity to build and lead a data engineering team.

• Full-time employment.