At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
We believe that our data is one of our greatest assets, and the insights we derive from it are crucial to our success. The Corporate Data and Analytics team’s mission is to enable trusted Analytics, Data Science, and AI for all Corporate functions, including Finance, Marketing, People, and Enterprise.
As a Senior Data Engineer, you will be a key technical leader on the team, owning the design, development, and operation of our critical data systems. You will drive engineering and operational excellence across the team, ensuring our data assets are high-quality, secure, and accessible for a variety of use cases.

EXPERIENCE:

• Required
• 5+ years of experience in data engineering and data platforms, particularly with cloud technologies like AWS, Databricks, and Snowflake.
• Expert-level proficiency in Python and SQL.
• Extensive experience with big data compute and storage technologies (e.g., Spark, Trino, Hive, Cloud Storage).
• Proven ability to apply full-scale software development practices to data, including test automation, CI/CD, and DevOps.
• Deep understanding of analytic and data needs within corporate functions like Finance, Marketing, Sales, and People.
• Expertise in creating and implementing frameworks and APIs for automating data management and governance.
• Track record of mentoring and leading other engineers, driving project execution, and collaborating with cross-functional partners.
• Preferred
• Experience with Graph databases, Vector databases, and Conversational analytics.
• Background in building Agentic applications for data engineering and operations.

• Leadership & System Ownership
• Lead the design, development, and operation of key data systems and pipelines, taking full ownership from ideation to production.
• Mentor junior engineers on best practices for data engineering, testing, and operational excellence.
• Drive collaboration with cross-functional partners (Product, Analytics, Data Science, and Business) to align on data needs and project priorities and deliver reliable data workflows
• Engineering & Operational Excellence
• Architect and build scalable batch and real-time data pipelines, ensuring data quality, security, and governance using Apache Airflow 2.0 and Astronomer.
• Lead architectural reviews and propose improvements to reduce complexity and operational burden.
• Drive post-incident investigations and lead efforts to resolve challenging issues and complete all resulting action items.
• Champion investments in architecture, observability, performance, and tooling to improve our systems and processes.
• Develop and optimize DAGs for reliability, performance, and maintainability.
• Planning & Execution
• Propose new projects and assist in prioritization, leveraging your deep understanding of the business and data needs.
• Break down complex work into manageable features and milestones, aligning dependencies for seamless execution.
• Deliver high-quality code and provide actionable, constructive feedback in code reviews.
• Create and promote thorough documentation of systems, designs, and processes to support knowledge sharing and onboarding.