Senior Data Engineer, Corporate Data and Analytics

Lyft; Toronto; Hybrid; CAD 136,000 - 170,000; Full time

Job summary

A leading transportation network company is seeking a Senior Data Engineer in Toronto, ON. This role involves designing and developing critical data systems, mentoring junior engineers, and ensuring data quality and security. The ideal candidate should have over 5 years of experience in data engineering and be proficient in Python and SQL. Benefits include comprehensive health coverage, flexible paid time off, and support for new parents.

Benefits

Extended health and dental coverage

Mental health benefits

Flexible paid time off

Commuter benefits

Qualifications

• 5+ years of experience in data engineering.
• Expert-level proficiency in Python and SQL.
• Deep understanding of data needs in corporate functions.

Responsibilities

• Lead the design and development of key data systems.
• Mentor junior engineers on best practices.
• Drive collaboration with cross-functional partners.

Skills

Data engineering

Cloud technologies (AWS, Databricks, Snowflake)

Python

SQL

Big data technologies (Spark, Trino, Hive)

Job description

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.

Responsibilities

• 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.

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.

Benefits

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $136,000 - CAD $170,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.