Senior Data Engineer, Growth

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

The Growth Team at Lyft focuses on acquiring and resurrecting riders and drivers efficiently to grow the business and balance the marketplace. We handle critical infrastructure to execute, manage, and optimize growth campaigns for the entire company and move quickly to test and develop new products.

As a Data Engineer on the Growth team, you will have ownership over the data architecture and pipelines that power Lyft's growth campaigns. Your efforts will be critical to the reliability of our pipelines, accurate reporting of campaign performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering.

Responsibilities:

• Own the data architecture and pipelines that support the operation and reporting of Lyft's growth campaigns.
• Evolve data models and schemas in response to business needs and engineering best practices
• Coordinate with cross-functional partners to understand business problems, align on project prioritization, and determine solutions that balance speed versus long-term functionality
• Assess and improve systems tracking data quality and consistency
• Implement and maintain tools for self-service data pipeline management (ETL)
• Conduct advanced performance tuning for SQL and MapReduce jobs to improve data processing performance

Experience:

• 5+ years relevant professional experience
• Experience with Hadoop (or similar) Ecosystem (MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase, Parquet)
• Proficient in at least one of the SQL languages (MySQL, PostgreSQL, SqlServer, Oracle)
• Good understanding of SQL Engine and able to conduct advanced performance tuning
• Strong skills in scripting language (Python, Ruby, Bash)
• 4+ years of experience with workflow management tools (Airflow, Oozie, Azkaban, UC4)
• Comfortable working cross-functionally to bridge Lyft's business goals with data engineering
• Strong communication and problem-solving skills.

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Access to a Health Care Savings Account
• In addition to provincial observed holidays, team members get 15 days paid time off, with an additional day for each year of service
• 4 Floating Holidays each calendar year prorated based off of date of hire
• 10 paid sick days per year regardless of province
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft proudly pursues and hires a diverse workforce. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter now if you wish to make such a request.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is $123,800-$172,000 CAD. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.