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.ResponsibilitiesOwn 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 scaleServe 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 ambitionsContinuously evolve data models and schemas to meet business and engineering requirementsDevelop AI tools that support self‑service management of data pipelines (ETL) and schema evolution,



and perform hands‑on SQL tuning to optimize data processing performanceWrite clean, well‑tested, and maintainable code, prioritizing scalability and cost efficiencyParticipate in code and architecture reviews to ensure code quality and distribute knowledgeManage on‑call rotations and proactively improve team processesMentor others, give brown bags, and promote engineering best practices across the teamExperiencesBachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field5+ years of professional experience in backend or data engineering with large-scale distributed systemsStrong 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)Solid data quality instincts, with hands‑on experience using tools like dbt, Great Expectations, or Monte Carlo to diagnose and resolve issues in complex datasetsExperience with workflow orchestration (e.G., Airflow, Prefect) and infra tooling (e.G., Terraform, Docker, Kubernetes), preferably in an AWS contextExperience designing API schemas and building backend services in a microservices architectureProficient and effective in using AI tools (e.G. Copilot, Claude Code, Cursor) to accelerate coding and engineering workflowsExcellent communication skills, with the ability to articulate technical concepts clearly to both technical and non‑technical audiences while collaborating effectively across teamsBonus: Experience with LLM orchestration or vector databases, or with experimentation/simulation platforms and A/B testing infrastructure at scaleBenefits:Extended health and dental coverage options, along with life insurance and disability benefitsMental health benefitsFamily building benefitsChild care and pet benefitsAccess to a Lyft funded Health Care Savings

📌 Senior Software Engineer, Data - Mapping (Toronto)
🏢 Lyft
📍 Toronto