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Data Engineer, Experimentation - job 1 of 2

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’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, build, and launch 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 several teams such as Analytics, Data Science, Marketplace, and many others.

Responsibilities:

  • Owner of the core company data pipeline, 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 systems tracking data quality and consistency
  • Develop tools supporting self-service data pipeline management (ETL)
  • SQL and MapReduce job tuning to improve data processing performance
  • Write well-crafted, well-tested, readable, maintainable code
  • Participate in code reviews to ensure code quality and distribute knowledge
  • Unblock, support and communicate with internal & external partners to achieve results

Experience:

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

Benefits:

  • Extended health and dental coverage options, along with life insurance and disability benefits
  • Mental health benefits
  • Family building benefits
  • Child care and pet benefits
  • Access to a Lyft funded Health Care Savings Account
  • RRSP plan to help save for your future
  • In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
  • Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
  • Subsidized commuter benefits

Lyft is committed to creating an inclusive workforce that fosters belonging. 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 if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. 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 $108,000-$135,000 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.

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What You Should Know About Data Engineer, Experimentation, Lyft

Join Lyft as a Data Engineer in Experimentation, based in the vibrant Toronto Coworking space, where your contribution will be pivotal in defining data-driven decisions. At Lyft, we believe that data forms the backbone of our operations, fueling insights that enhance our services and improve user experiences. As a Data Engineer, you’ll dive into our core data pipeline, overseeing and optimizing the structure that supports Lyft’s analytics and product features. With over three years of relevant experience, you’ll utilize your expertise with Hadoop and scripting languages such as Python or Ruby to build scalable data platforms that can handle increasing data loads and provide seamless access to vital business metrics. You’ll collaborate closely with data analytics teams to ensure that our data architectures perfectly align with business goals. Whether tracking data quality or evolving database schemas, your role influences the future of transport experience. You’ll enjoy a flexible workplace with a hybrid schedule and a generous benefits package that acknowledges your work-life balance. This is not just a job; it’s a chance to be part of a dynamic team at a cutting-edge company dedicated to connecting people and communities through the power of data. Let’s make an impact together at Lyft!

Frequently Asked Questions (FAQs) for Data Engineer, Experimentation Role at Lyft
What responsibilities does a Data Engineer at Lyft have?

As a Data Engineer at Lyft, you'll own the company's core data pipeline, responsible for scaling up data processing flows. You'll be tasked with evolving data models, implementing systems to track data quality, and developing tools for self-service data management. In essence, you will play a vital role in ensuring that data remains a top priority at Lyft.

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What qualifications are needed to apply for the Data Engineer position at Lyft?

Applicants for the Data Engineer role at Lyft should have at least three years of relevant experience, with familiarity in Hadoop or similar ecosystems. It's important to possess strong skills in a scripting language like Python or Ruby and to be well-versed in SQL for database management. Experience with workflow management tools is also key for this position.

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How does Lyft support a flexible work-life balance for Data Engineers?

Lyft promotes a healthy work-life balance for its Data Engineers through a hybrid work model, requiring in-office presence three days a week, along with options for remote work. Additionally, the company offers flexible paid time off policies and generous parental leave to support employees in managing their personal lives alongside their professional careers.

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What benefits can a Data Engineer expect at Lyft?

Data Engineers at Lyft enjoy an attractive benefits package, including extensive health and dental coverage, mental health benefits, child care support, and generous paid time off. Lyft also offers an RRSP plan for retirement savings and subsidized commuter benefits, enhancing the overall work experience.

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What role does collaboration play in the Data Engineer position at Lyft?

Collaboration is crucial for a Data Engineer at Lyft. You'll work directly with data analytics teams to bridge business goals with engineering efforts. Regular communication with both internal and external partners ensures that your insights and solutions remain aligned with company objectives, making teamwork a central aspect of the role.

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Common Interview Questions for Data Engineer, Experimentation
Can you describe your experience with data pipelines?

In answering this question, share specific projects where you've built or optimized data pipelines. Highlight relevant technologies you've used, your role in managing data flow, and any challenges you overcame during the process.

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How do you ensure data quality and consistency?

Discuss methods you've used for monitoring data quality, like automated checks or validation routines, and how you've implemented systems to maintain data integrity over time. Provide examples when possible to illustrate your approach.

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What is your process for performance tuning SQL queries?

When explaining your process, emphasize tools and techniques you use for performance tuning, such as indexing, query optimization, and analyzing execution plans. Sharing metrics on performance improvements will strengthen your response.

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What scripting languages are you comfortable with, and how have you used them in data engineering?

Highlight your proficiency in scripting languages like Python or Ruby and provide examples of how you've automated tasks, handled data manipulation, or built ETL processes using these languages in previous roles.

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Describe your experience with Hadoop or similar ecosystems.

Use this opportunity to showcase specific projects where you utilized Hadoop and related tools, such as Hive or Spark. Discuss the scale of data you've worked on and the outcomes achieved through these technologies.

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How do you keep up with the latest trends and technologies in data engineering?

Address this question by mentioning relevant blogs, forums, online courses, or conferences you follow or attend. Explain how this ongoing learning has influenced your work and decision-making in previous positions.

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Can you give an example of a complex problem you solved?

Prepare a STAR method response (Situation, Task, Action, Result) to discuss a particularly challenging problem you've encountered. Focus on how your data engineering skills enabled you to craft a successful solution.

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Share your experience with workflow management tools.

Discuss any workflow management tools you’ve used, like Airflow or Oozie. Describe how you've utilized them to schedule tasks, manage dependencies, or monitor workflows, including any optimizations you’ve achieved.

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What strategies do you use to ensure scalability in data models?

Explain your approach to designing scalable data architectures, referencing principles like normalization, denormalization, and flexible schema design. Provide examples of how you've built systems that grow as data needs evolve.

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How do you approach collaborations with analytics teams?

Share strategies you employ for effective communication with analytics teams, including how you gather requirements, clarify objectives, and ensure that your data engineering efforts align with their analysis goals.

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Lyft is one of the leading ride-sharing companies in America offering services in ride-hailing, vehicles for hire, motorized scooters, a bicycle-sharing system, rental cars, and food delivery in the United States and select cities in Canada.

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BADGES
Badge ChangemakerBadge Diversity ChampionBadge Flexible CultureBadge Work&Life Balance
CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Customer-Centric
Social Impact Driven
Rapid Growth
BENEFITS & PERKS
Maternity Leave
Paternity Leave
Flex-Friendly
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
401K Matching
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
April 3, 2025

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