Data Engineer

Summary

Join Lyft's Data Engineering team as a key contributor to building and maintaining scalable data infrastructure. You will be responsible for data transport, collection, and storage systems, ensuring data is a first-class citizen. This early-stage team focuses on developing pipelines supporting Lyft's top-line metrics and decision-making processes for finance, pricing, and driver-related metrics. Collaborate with cross-functional teams to evolve data models and architectures, enabling seamless access to insights for Analytics, Data Science, and Engineering. You will take ownership of core data pipelines and contribute to the team's technical roadmap. This fully remote role is based in Ukraine.

Requirements

• 5+ years of professional experience in data engineering or a related field
• Strong expertise in SQL and experience with Spark and/or PySpark
• Proficiency in a scripting language like Python or Bash
• Strong data modeling skills and a deep understanding of ETL processes
• Experience building and optimizing complex data models and pipelines
• Hands-on experience with workflow management tools (e.g., Airflow or similar)
• Familiarity with Trino SQL (for data quality checks) and a basic understanding of SQS

Responsibilities

• Take ownership of core data pipelines, ensuring resilience, optimal performance, timely delivery, data quality, and seamless onboarding of new features
• Continuously evolve data models and schemas to meet business and engineering requirements
• Implement and maintain systems to monitor and enhance data quality and consistency
• Develop tools that support self-service management of data pipelines (ETL) and perform SQL tuning to optimize data processing performance
• Contribute to the Data Engineering team’s technical roadmap, ensuring alignment with team and stakeholder goals
• Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency
• Conduct code reviews to uphold code quality standards and facilitate knowledge sharing
• Participate in on-call rotations to maintain high availability and reliability of workflows and data pipelines
• Collaborate with internal and external partners to remove blockers, provide support, and achieve results

Preferred Qualifications

Nice to have experience working directly with cross-functional teams (data analytics, data science, engineering) to align data engineering solutions with business goals

Benefits

• Professional and stable working environment
• The latest technology and equipment you need
• Potential to work remotely, including out of country (dependent on work authorizations)
• 28 calendar days for vacation and up to 5 sick days
• 18 weeks of paid parental leave. Biological, adoptive and foster parents are all eligible
• Mental health benefits
• Family building benefits