Summary

The Lead Analytics Engineer (L3) is responsible for driving analytics engineering initiatives and delivering high-quality data models that enable data-driven decision making across the organization. This role requires deep technical expertise in analytics engineering, strong independent execution capabilities, and exceptional cross-functional collaboration skills. The Lead Analytics Engineer will report to the Senior Manager of Analytics Engineering and serve as a key technical contributor and partner to business stakeholders, data analysts, and engineering teams.

Responsibilities

• Designing, developing, and maintaining scalable data models and transformations using dbt and SQL to support analytics and reporting needs.
• Independently owning end-to-end analytics projects from requirements gathering through deployment and documentation.
• Partnering closely with business stakeholders, data analysts, and product teams to understand analytical requirements and translate them into robust data solutions.
• Building and optimizing semantic layers, metrics frameworks, and reusable data models that serve as the foundation for self-service analytics.
• Establishing and enforcing analytics engineering best practices including testing, version control, code reviews, and documentation standards.
• Collaborating with data engineers to ensure efficient data pipeline integration and with BI teams to enable effective reporting and visualization.
• Proactively identifying data quality issues, implementing data tests, and monitoring model performance to ensure reliability.
• Communicating technical concepts effectively to both technical and non-technical audiences, including presenting solutions and trade-offs to stakeholders.
• Contributing to the analytics engineering roadmap by identifying opportunities for process improvements and technical innovations.
• Mentoring junior analytics engineers and analysts on SQL, dbt, and analytics engineering principles.

Requirements

• Bachelor's degree in a quantitative field (Computer Science, Statistics, Mathematics, Data Analytics) or equivalent experience.
• 5+ years of experience in analytics engineering, data analytics, or related roles with increasing technical responsibility.
• Expert-level SQL skills with deep understanding of data modeling, dimensional modeling, and database optimization techniques.
• Strong hands-on experience with dbt including macros, packages, testing frameworks, and deployment workflows.
• Proven ability to work independently, manage multiple priorities, and deliver high-quality results with minimal supervision.
• Exceptional cross-functional collaboration skills with demonstrated success partnering with business stakeholders to solve complex problems.
• Strong communication skills with the ability to translate business requirements into technical specifications and explain technical solutions to diverse audiences.
• Experience with data warehousing platforms (Snowflake, BigQuery, Redshift) and version control systems (Git).
• Understanding of data pipeline concepts, orchestration tools, and the broader data ecosystem.
• Self-motivated learner with a track record of staying current with analytics engineering best practices and emerging technologies.
• Ability to balance technical excellence with business impact, making pragmatic trade-offs when necessary. Proven ability to work collaboratively with cross-functional teams and translate business requirements into technical solutions.

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