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.

Here at Lyft, Data is the only way we make decisions. It is the core of our business, helping us create a transportation experience for our customers, and providing insights into the effectiveness of our product launch & features.

As a Data Engineer at Lyft, you will be a part of an early-stage team that builds the data transport, collection, and storage, and exposes services that make data a first-class citizen at Lyft. We are looking for a Data Engineer to build a scalable data platform. You will proactively propose new ideas, evaluate multiple approaches and choose the best one based on fundamental qualities and supporting data. Communicate highly technical problems, working along with our cross-functional team. You’ll have ownership of our core data pipeline that powers Lyft’s top-line metrics; You will also use data expertise to help evolve data models in several components of the data stack; You will help architect, building, and launching scalable data pipelines to support Lyft’s growing data processing and analytics needs. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel various teams such as Analytics, Data Science, Engineering, and many others. 

Responsibilities:

Own of the core company data pipeline, be responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement and adopt systems tracking data quality and consistency Propose and develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Drive the DE team tech roadmap and align it to the team and stakeholders Build well-crafted, well-tested, readable, maintainable code with data infrastructure cost and scalability in mind  Participate in code reviews to ensure code quality and distribute knowledge Participate in on-call rotations to ensure high availability and reliability of workflows and data Unblock, support and communicate with internal & external partners to achieve results

Experience:

5+ years of relevant professional experience Strong experience with Spark and SQL Strong skills in a scripting language (Python, Bash, etc) Experience with some of the following: Hadoop (or similar) Ecosystem, S3, DynamoDB, MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase, Parquet Experience of driving building complex data models and pipelines 2+ years of experience with workflow management tools (Airflow or similar) Nice to have experience of working directly with cross-functional data analytics, data scientists, and engineering teams to bridge Lyft’s business goals with data engineering

Benefits:

Professional and stable working environment. 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.

This role is fully remote in Ukraine, candidates for this role must be based in Ukraine. #Remote