Data Engineer
Builds and owns scalable data pipelines, models, and integrations supporting Lyft’s Safety and Customer Care platforms. The role requires 4+ years of data engineering experience, strong Spark, Python, and SQL skills, and familiarity with distributed data systems and AWS tooling.
About the job
Responsibilities
- Own the core data pipeline and scale data processing flows to meet rapid data growth.
- Evolve data models and schemas based on business and engineering needs.
- Implement systems to track data quality and consistency.
- Develop self-service tools for data pipeline management and ETL.
- Tune SQL and MapReduce jobs to improve data-processing performance.
- Write well-crafted, well-tested, readable, and maintainable code.
- Participate in code reviews to ensure code quality and distribute knowledge.
- Collaborate with product, engineering, data science, and marketing teams to understand business problems and align on priorities and solutions.
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
- 4+ years of professional experience in data engineering, ideally with large-scale distributed systems.
- Strong skills in Spark, Python or a similar scripting language, and SQL performance tuning.
- Experience with AWS, Hadoop/S3, Hive, Presto, Airflow, and related tools.
- Solid understanding of ETL processes, workflow orchestration, and data warehousing.
- Collaborative mindset and comfort working across teams to solve real-world problems.
Compensation and Benefits
- Expected base pay range in the Toronto area: CAD $108,000–$135,000.
- Extended health and dental coverage, life insurance, and disability benefits.
- Mental health benefits.
- 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; hourly team members receive 15 days paid time off, plus an additional day per year of service.
- 18 weeks of paid parental leave as a top-up to provincial programs for eligible biological, adoptive, and foster parents.
- Subsidized commuter benefits and Lyft ride credits.
Skills
Spark, Python, SQL, AWS, Hadoop, Amazon S3, Hive, Presto, Apache Airflow, Mapreduce, ETL, Workflow Orchestration, Data Warehousing, Data Modeling, Data Quality
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