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Canada
Remote only
As the largest global shared micromobility business, Lime is on a mission to build a future where transportation is shared, affordable and carbon-free. A Time Magazine 100 Most Influential Company, Lime has powered more than one billion rides in close to 30 countries across five continents, spurring a new generation of clean alternatives to car ownership. Learn more at li.me.
The Data Engineering team architects, builds, and scales the foundational data infrastructure that powers our global fleet’s analytics, machine learning models, and real-time business intelligence. We are looking for a Senior Data Engineer to independently lead the delivery of reliable, scalable data products and solve difficult challenges in data quality, governance, and distributed processing.
This is a remote position with a requirement for candidates to reside in Canada to maintain effective collaboration across teams.
What You’ll Do:
Own the end-to-end design, delivery, and operation of major data products, including high-throughput ETL/ELT pipelines, transformation workflows, and storage solutions.
Partner with engineering, product, and business stakeholders to clarify requirements, challenge assumptions, define pragmatic solutions, and drive projects from design through production launch.Solve difficult data engineering problems by developing performance-tuned transformations and services using Python, high-performance SQL, and tools such as dbt.
Make sound technical trade-offs at the product level, balancing scalability, reliability, delivery speed, maintainability, and cost.
Author and drive technical designs and RFCs that clearly communicate architecture, alternatives, risks, and operational considerations.
Influence the technical direction of the data products you own and contribute to the team’s broader technical strategy and roadmap.
Set a high quality bar through thoughtful design and code reviews, automated testing, version-controlled schemas, and CI/CD practices for data pipelines.
Lead projects that improve the team’s engineering and operational excellence, including data observability, lineage, incident response, deployment safety, and developer productivity.
Design and operate scalable batch and real-time data solutions using technologies such as Spark, Flink, and Kafka.
Partner with the ML Platform team to deliver clean, reliable, and feature-rich datasets for model training and inference.
Advance data stewardship through strong documentation, discoverability, privacy controls, access management, and governance practices.
Lead postmortems for data incidents, identify systemic improvements, and drive corrective actions to completion.
Break complex projects into clear, deliverable work and help coordinate execution across engineers on the team.
Mentor other engineers, provide actionable technical feedback, and participate in interviewing and hiring.
About You:
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.
5+ years of relevant industry experience in data engineering, distributed systems, or a related field.
A track record of independently delivering and operating significant production data products end to end.
Experience using AI-assisted development tools to support coding, debugging, testing, documentation, technical exploration, and analysis.
Ability to validate AI-assisted outputs, identifying risks and failure modes, protecting sensitive information, and knowing when deeper manual review is required.
Deep experience building and scaling cloud-based data platforms, preferably using AWS and Snowflake.
Expertise in developing, optimizing, and debugging complex data transformations using Python and high-performance SQL.
Strong understanding of data modeling, ETL/ELT architecture, schema design, and transformation frameworks such as dbt.
Experience designing reliable workflows using orchestration tools such as Airflow.
Hands-on experience with distributed processing or streaming technologies such as Spark, Flink, or Kafka.
Strong technical judgment and experience making trade-offs among performance, reliability, scalability, maintainability, and cost.
Experience establishing or improving data quality, testing, observability, lineage, and operational practices.
Familiarity with modern data governance practices, including cataloging, data classification, PII masking, privacy controls, and access management.
Experience writing technical design documents and communicating complex decisions to technical and non-technical stakeholders.
Experience with technologies such as Iceberg, Debezium, or infrastructure-as-code tools such as Terraform is a plus.
The base salary range listed reflects what Lime reasonably expects to offer for this role, with the final base salary determined by objective factors such as the candidate’s location and relevant skills and experience. Depending on the position, the total compensation package may also include discretionary annual performance bonus opportunities and equity, subject to applicable plan terms and eligibility requirements.
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If you want to make an impact, Lime is the place for you. Not sure if you meet all the qualifications? If this role excites you we encourage you to apply. Explore all opportunities on our career page.
Lime is proud to be an Equal Opportunity Employer. We believe different perspectives help us grow and achieve more. That’s why we’re dedicated to building and developing a team that reflects a wider range of backgrounds, abilities, identities, and experiences. If you require a reasonable accommodation during the application or hiring process, please email recruiting-operations@li.me for assistance.