Senior Data Engineer

TBS - Data Engineering

At Lyft, our mission is to enhance people's lives with the world's best transportation. To achieve this, we commence with our own community by building an open, inclusive, and diverse organization.

At Lyft, Data is our key decision-making tool. It sits at the core of our business, assisting us in creating a transportation experience for our customers and offering insights into the effectiveness of our product releases & features.

This team centrally focuses on supporting our business by developing the data transportation, gathering, and storage that underpins our Transit, Bikes, and Scooters business. We are seeking a Data Engineer to create scalable solutions, leveraging their data expertise and our technological stack to deliver timely, accurate data for our internal and external customers. You will get the chance to be a part of a new, expanding sector of our micro mobility platform. This role entails collaboration with product managers, external stakeholders, GMs, engineers, and data scientists to gather and translate requirements into solutions, ensuring data-driven decision-making lies at the heart of our operations.

This role reports to the Engineering Manager.

Responsibilities:

• Ownership of core company data pipelines, tasked with scaling up data processing flow to match the swift data growth at Lyft
• Evolve data model and data schema according to business and engineering needs
• Implement systems for tracking data quality and consistency
• Develop tools that support self-service data pipeline management ()
• SQL and MapReduce job tuning to enhance data processing performance
• Compose well-designed, thoroughly tested, readable, maintainable code
• Participate in code reviews to ensure code quality and share knowledge
• Unblock, assist, and communicate with internal & external partners to achieve results

Experience:

• 5+ years of relevant professional experience
• Experience with Hadoop (or like) Ecosystem (MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase, Parquet)
• Proficient in at least one of the SQL languages (MySQL, PostgreSQL, SqlServer, Oracle)
• A deep understanding of SQL Engine and can conduct advanced performance tuning
• Strong skills in scripting languages (Python, Ruby, Bash)
• 2+ years of experience with workflow management tools (Airflow, Oozie, Azkaban, UC4)
• Comfortable working directly with data analytics to connect Lyft's business goals with data engineering

Benefits:

• Additional options for health and dental coverage, accompanied by life insurance and disability benefits
• Mental health benefits
• Besides provincially observed holidays, team members receive 15 days paid time off, with an extra day for each service year
• 4 floating holidays each calendar year proportionate to the date of hire
• 10 paid sick days each year irrespective of province
• Family building benefits
• Access to a Health Care Savings Account
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft staunchly promotes and employs a diverse workforce. Lyft holds the belief that everyone has the right to equal employment opportunities devoid of discrimination due to race, ancestry, place of origin, color, ethnic origin, citizenship, religion, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offenses, or any other grounds protected by the applicable law or by the company's policy. Lyft also strives for a safe and healthy workplace and strictly forbids any form of harassment. Accommodation for persons with disabilities will be provided upon request in alignment with applicable laws during the application and hiring process. Please contact your recruiter now if you wish to make such a request.

Starting in September 2023, this role will require office presence on a hybrid schedule — Team Members will be expected to work in the office thrice a week on Mondays, Thursdays, and a team-specific third day. Besides, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per annum.