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Lyft

Senior Software Engineer, Data Platform

Posted 8 Days Ago
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In-Office
Toronto, ON
Senior level
In-Office
Toronto, ON
Senior level
Design, develop, and maintain high-performance low-latency streaming systems for critical applications, while leading projects and collaborating with teams.
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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. 

We are seeking a talented Software Engineer to join our dynamic Streaming Compute Team. In this role, you'll be instrumental in designing, developing, and maintaining our low latency and high throughput systems, which are critical to a lot of teams like driver, mapping, fraud etc. and almost all ML models at Lyft. Our systems and platform are used for a variety of use cases such as, persisting high volume service events, detecting issues with routes, computing prime-time, creating, storing and serving ML features for training and inference purposes for teams like payments, incentives etc. The majority of our streaming solutions run on Apache Flink and Apache Beam with support from reading and writing to various sources and sinks respectively.

As a Software Engineer,  you will lead the team’s projects and initiatives seeing them to completion. You will be responsible for key systems and components within the team. You will identify and lead the efforts in improving architecture and operations for the team.

We are looking for candidates who have prior experience with near-real-time streaming systems, are self-starters, and have a proven track record of delivering high-quality software solutions that solve critical business needs. The candidate should be able to dive deep into problems with lots of ambiguity, leading architectural design and building robust, well-tested technical solutions. They should be willing to take complete ownership of a project or a feature, able to drive it from design and implementation through to operational excellence, while also mentoring others, improving team engineering practices, and collaborating effectively with partners.

Responsibilities:
  • Design, develop, deploy, monitor, operate and maintain scalable streaming solutions that constitute our streaming platform
  • Work with technologies such as Apache Kafka, Flink, Beam etc.  to enhance our data platform's streaming offerings
  • Collaborate with cross-functional teams to integrate streaming solutions into the broader data architecture
  • Analyze our internal systems and processes and locate areas for improvement/automation
  • Collaborate with product org stakeholders to address and prioritize custom edge cases
  • Help lead large projects from inception to positive execution
  • Operate a real-time streaming platform with high availability and low downtime to meet the demands of latency-sensitive workloads.
Experience:
  • 5+ years of experience with building, deploying and maintaining low latency, high throughput services
  • 5+ years of experience building and developing large-scale infrastructure, distributed systems or networks, and/or experience with compute technologies
  • 3+ years of software engineering industry experience and with distributed streaming solutions like Apache Flink, Beam, Spark streaming, Streaming SQL etc.
  • Experience working with kubernetes and container technologies (e.g. Docker, cri-o, etc)
  • Familiar with a cloud-based environments such as AWS/GCP/Azure
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 CAD $136,000 - CAD $170,000. 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.

Top Skills

Apache Beam
Apache Flink
Apache Kafka
AWS
Azure
Docker
GCP
Kubernetes

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