Lead Analytics Engineer

Columbus, OH

About the position

The Lead Analytics Engineer at Safelite is instrumental in developing, building, maintaining, and evolving the company's data warehouse infrastructure to enhance data availability for the business. This role is responsible for implementing, managing, and scaling modern data warehouse pipelines using tools like git, dbt, and airflow in a dual-stack data environment actively transitioning to cloud-based infrastructure. Additionally, the Lead Analytics Engineer will guide the team in transforming raw data into clean, usable datasets, ensuring data quality and reliability through strong SQL skills and software engineering practices. The expected outcome is a robust and reliable data infrastructure that supports business decision-making and aligns with Safelite's best practices.

Responsibilities

• Drive the development and maintenance of our data warehouse to accelerate data availability for data and business analysts embedded throughout the organization.
• Own and champion cross-functional, centralized 'crown jewel' data assets that answer Safelite's most critical operational questions, reinforcing them as the Source of Truth across the organization.
• Apply software engineering best practices to uplift analytics processes and develop scalable data models that enable performant analysis into Safelite's business.
• Codify and democratize best practices for SQL query optimization/reusability and reporting, leveraging Safelite's data assets, and analytics development within Snowflake SQL, dbt, and git.
• Define teamwide coding standards, documentation requirements, and development processes (code reviews, testing requirements, etc.).
• Collaborate closely with Safelite's BI and Data Engineering teams to improve the usability, quality, and reliability of data for the business.
• Work with the data team and embedded analysts and business SMEs to develop and maintain data quality rules, documentation, and definitions.
• Scope requirements with internal stakeholders and lead working groups to usher projects through their entire lifecycle while building clear roadmaps for cross-functional team members.
• Support the buildout of executive facing collateral showcasing the evolving data strategy and practical business impacts.
• Perform other duties as assigned.
• Comply with all policies and standards.

Requirements

• Bachelor's Degree in computer science, engineering, analytics, or related field.
• 7-9 years hands on experience in a data engineering or analytics related role.
• Deep knowledge and experience with advanced SQL concepts including window functions, CTEs, nested queries, and other similar techniques.
• 7+ years of hands-on experience with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery) and relational databases.
• Deep understanding of multi-step ETL and ELT jobs/data pipelines and experience working with job scheduling systems.
• Extensive experience independently building and optimizing highly complex data pipelines, architectures, and data sets.
• Strong understanding of the analyst’s workflow as it relates to both structured and unstructured datasets.

Nice-to-haves

• Exposure to data pipeline and workflow management tools (e.g., Airflow, Dagster).
• Experience with script-based analytics transformation tools (e.g., dbt, AWS Glue, Talend).
• Experience with Python or similar programming language.
• Ability to collaborate through code-management/version control tools like GitHub Enterprise.
• Prior experience with large enterprise legacy tooling (e.g., mainframe, Informatica, Oracle Business Intelligence, Cognos).
• Conceptual knowledge and expertise with Tableau or equivalent BI visualization tool (e.g., Qlik, Power BI).