Lyft
Mid
Own the data pipelines that power real-time and strategic ride pricing at Lyft
Lyft's Pricing team is hiring a Data Engineer in Toronto to build and scale the data foundation behind pricing decisions — demand forecasts, marketplace signals, promotions, and cost models. You'll own pipeline scaling as data grows, evolve data models/schemas, build data-quality tracking and self-service ETL tooling, and tune Spark/SQL jobs for performance, working on an AWS/Kubernetes/Airflow stack alongside data science and ML partners.
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What this interview tests
- Scalable data pipeline architecture (Spark, Hadoop ecosystem: S3, Hive, Presto, HDFS)
- SQL and MapReduce/Spark job performance tuning
- Data model/schema evolution without breaking downstream consumers
- Workflow orchestration (Airflow) and self-service ETL tooling
- Data quality and consistency monitoring
- Cross-functional communication with data science, engineering, and business partners
Common question themes
Design or scale a data pipeline for a rapidly growing data volume
Diagnose and fix a slow Spark/SQL job (skew, partitioning, shuffle)
Evolve a data schema under changing requirements without breaking consumers
Build self-service ETL/data quality tooling for other teams
Debug a data consistency or quality issue in a pricing-relevant pipeline
Explain a technical data constraint to a non-technical business partner
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