Lyft

Technology

EngineeringManagerDataPlatform

CA$172–215k Toronto, Ontario, Canada Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Manager candidates.

The Brief

“Engineering Manager – Data Platform at Lyft. Skills: Data Platform, Lakehouse architecture, Engineering leadership. Lead foundational data layer team. Manage catalog and metadata”

What You'll Achieve.

Ensure systems remain reliable; Ensure systems remain scalable; Ensure systems remain well-understood

Industry & Context.

Technology
Problems you'll solve

Ambiguity; High-stakes situations

What They're Looking For.

Must Have

3+ years Engineering Manager experience, Lead teams of 5+ engineers, Experience managing data infrastructure teams, Experience managing data platform teams, Technical background for architecture discussions, Experience building inclusive teams

Nice to Have

Experience with lakehouse architectures, Experience with Databricks, Experience with Snowflake, Experience with Delta table formats, Experience with Iceberg table formats, Experience with Hudi table formats, Experience with Unity Catalog migration, Experience with distributed teams

What You'll Do.

Lead foundational data layer team

Manage catalog and metadata

Manage gateway and access patterns

Drive lakehouse modernization

Migrate to Unity Catalog

Converge metadata across data stack

Partner with Data Platform teams

Partner with engineering organizations

Define team's technical direction

Balance platform investment

Ensure layer reliability

Guide engineer development

Foster team ownership

Make effective decisions

Demonstrate technical rigor

Foster cross-team engagement

Partner with customers

Recognize contributions

Ensure clear expectations

Own team deliverables

Maintain foundational systems

How You'll Work.

Team & Collaboration

Peer Data Platform teams; Engineering organizations; Adjacent teams; Cross-team engagement

Communication Scope

Written communication; Verbal communication; Strategic level communication

Process & Methodology

Platform migrations, Architectural transitions

Full Job Description

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. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

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