Manager, Analytics Engineering

What You Will Work On

• Lead and develop a team of analytics engineers, fostering their professional growth through goal-setting, coaching, feedback, and recognition.
• Guide your team in designing, implementing, and maintaining scalable data models and ELT pipelines, a star schema architecture, and reporting solutions that power business intelligence, reduce time to insights, and elevate our company-wide data literacy.
• Manage project priorities and timelines for your team, ensuring the timely delivery of rigorous, impactful solutions while upholding high standards for data quality and integrity.
• Collaborate with Data & Analytics leadership and cross-functional teams (including Engineering, Operations, and business teams) to understand requirements and translate them into executable analytics engineering projects and data products.
• Contribute to the data strategy and roadmap by identifying opportunities and executing projects leveraging data modeling, data warehouse architecture, and other analytics engineering best practices.
• Uphold and contribute to best practices for data model development, testing, and documentation within your team to deliver iteratively and efficiently.
• Build relationships with cross-functional leads to promote the adoption of new methods, technologies, and self-service data tools that help the organization scale.

Qualifications

• 7+ years of experience in a data role such as analytics engineering, data engineering, or data warehousing, with hands-on experience designing and building scalable data models and ETL/ELT pipelines.
• 2+ years in people management, with a proven track record of developing and managing high-performing teams.
• Proficiency in SQL and Python.
• Deep expertise in data warehouse architecture and dimensional modeling (e.g., Kimball).
• Demonstrated experience with a modern data stack, preferably Snowflake, Airflow, and dbt.
• Strong analytical and problem-solving skills, with the ability to work with complex datasets to transform and model them for analytical use.
• Excellent oral & written communication skills and a strong ability to collaborate with both technical and non-technical stakeholders.
• Strong project management skills, with the ability to manage multiple projects, prioritize effectively, and meet deadlines.