Senior Software Engineer, Data - Mapping
Leads architecture for offline experimentation and route simulation while building reliable, scalable data pipelines and backend services. The role requires 5+ years of backend or data engineering experience, distributed-systems expertise, strong SQL and Spark skills, and proficiency with modern cloud infrastructure.
About the job
Responsibilities
- Own core data pipelines end-to-end, building subject-matter expertise and defining and managing SLAs for pipelines, services, and datasets.
- Lead architecture and technical direction for offline experimentation and route simulation services.
- Evolve data models and schemas to meet business and engineering requirements.
- Develop AI tools for self-service ETL pipeline management and schema evolution.
- Tune SQL queries to optimize high-volume data processing.
- Write scalable, cost-efficient, well-tested, and maintainable code.
- Participate in code and architecture reviews.
- Manage on-call rotations and improve team processes.
- Mentor colleagues and promote engineering best practices.
Requirements
- 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 a scripting language such as Python, Ruby, or Bash.
- Experience with distributed storage, querying, and streaming technologies.
- Strong SQL skills and advanced performance-tuning experience with high-volume event data.
- Experience diagnosing and resolving data-quality issues in complex datasets.
- Experience with workflow orchestration and infrastructure tooling, preferably in an AWS context.
- Experience designing API schemas and building backend services in a microservices architecture.
- Proficiency using AI tools to accelerate coding and engineering workflows.
- Excellent communication and cross-functional collaboration skills.
Nice-to-haves
- Experience with LLM orchestration or vector databases.
- Experience with experimentation or simulation platforms and large-scale A/B testing infrastructure.
Compensation and Benefits
- Base pay range: CAD $136,000–$170,000 in the Toronto area, excluding potential equity, bonus, and benefits.
- Extended health and dental coverage, life insurance, and disability benefits.
- Mental health, family building, child care, and pet benefits.
- Lyft-funded Health Care Savings Account.
- RRSP plan with company match.
- Flexible paid time off for salaried team members.
- Paid parental leave, subsidized commuter benefits, and Lyft ride credits.
- Hybrid schedule requiring at least three days per week in the office.
Skills
Spark, Python, Ruby, Bash, ClickHouse, Hive, Presto, Delta Lake, Apache Iceberg, Apache Kafka, SQL, dbt, Apache Airflow, Terraform, Docker
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