Senior Software Engineer, Data - Mapping

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

Benefits offered by this job

Extended health and dental coverage

Mental health benefits

Family building benefits

Child care and pet benefits

Lyft Health Care Savings Account

Job summary

Lyft is seeking a Senior Software Engineer, Data for the Mapping team in Toronto. You will lead data pipelines end-to-end, own the offline experimentation platform, and drive route simulation services to test changes safely before production.

You will build scalable data pipelines for experimentation and analytics, enabling data-informed decisions across teams. You will work with Spark, SQL, and AI tools, collaborate with engineers, data scientists, and product managers, and contribute to

Qualifications

• Bachelor's degree in CS/Engineering/Math/Stats or related field.
• 5+ years of backend or data engineering with large-scale distributed systems.
• Strong SQL skills (MySQL/PostgreSQL) with high-volume data.
• Experience with Spark and scripting languages (Python, Ruby, Bash).
• Experience with data quality tools and workflow orchestration.

Responsibilities

• Own core data pipelines end-to-end with SLAs for reliability at scale.
• Lead architectural direction for offline experimentation platform and route simulations.
• Evolve data models and schemas to meet business needs.
• Develop AI tools to manage data pipelines and perform SQL tuning.
• Write clean, scalable, well-tested code and participate in reviews.

Skills

Spark

Python

Ruby

Bash

SQL

Kafka

Airflow

Kubernetes

Terraform

API design

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related field

Tools

dbt

Great Expectations

Monte Carlo

Airflow

Terraform

Docker

Kubernetes

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.

As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability.

Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers.

Responsibilities

• Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale
• Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions
• Continuously evolve data models and schemas to meet business and engineering requirements
• Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform hands-on SQL tuning to optimize data processing performance
• Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency
• Participate in code and architecture reviews to ensure code quality and distribute knowledge
• Manage on-call rotations and proactively improve team processes
• Mentor others, give brown bags, and promote engineering best practices across the team

Experiences

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• 5+ years of professional experience in backend or data engineering with large-scale distributed systems
• Strong experience with Spark, and with a scripting language (Python, Ruby, Bash)
• Experience with distributed storage, querying, and streaming technologies (e.g. Clickhouse, Hive, Presto, Delta, Iceberg, Kafka)
• Strong SQL skills (MySQL, PostgreSQL or similar), with experience conducting advanced performance tuning and querying high volume events data (e.g. geospatial, behavioural)
• Strong data quality instincts, with hands-on experience using tools like dbt, Great Expectations, or Monte Carlo to diagnose and resolve issues in complex datasets
• Experience with workflow orchestration (e.g., Airflow, Prefect) and infra tooling (e.g., Terraform, Docker, Kubernetes), preferably in an AWS context
• Experience designing API schemas and building backend services in a microservices architecture
• Proficient and effective in using AI tools (e.g. Copilot, Claude Code, Cursor) to accelerate coding and engineering workflows
• Excellent communication skills, with the ability to articulate technical concepts clearly to both technical and non-technical audiences while collaborating effectively across teams
• Bonus: Experience with LLM orchestration or vector databases, or with experimentation/simulation platforms and A/B testing infrastructure at scale

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 with company match 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 and Lyft ride credits

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, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.