Role overview

Lightspeed’s Data Office is seeking a Senior Analytics Engineer to design and build the data models that underpin business decisions across finance, go-to-market strategy, and product insights. You will partner with stakeholders across Finance, Revenue Ops, Marketing, and Product to create the analytics foundation the organization relies on.

Key responsibilities

Design and build data models that power financial reporting, revenue metrics, go-to-market analytics, and product and operational insights across the business.
Translate ambiguous business requirements from multiple teams into well-scoped technical solutions with clear effort estimates.
Collaborate across a Hub & Spoke architecture with upstream data owner teams, downstream analytics developers, and domain-specific pods to ensure models work end-to-end.
Create and maintain documentation as a first-class deliverable, including column descriptions, model contracts, and architectural notes that support both human reviewers and AI-assisted workflows.
Diagnose root causes of data issues and drive systemic fixes rather than temporary patches, while monitoring pipeline health proactively and leading incident response.
Mentor junior engineers through code reviews and technical sessions, setting quality standards for the team.
Manage personal sprint commitments autonomously and contribute to team-level planning through task breakdown, estimation, and priority sequencing.

Requirements

Expert-level SQL proficiency, including query performance optimization, clean and maintainable code, and advanced analytical techniques such as window functions.
Proven experience designing enterprise-grade dimensional models on modern cloud data warehouses like BigQuery or Snowflake, with expertise in partitioning, incremental patterns, and performance optimization.
Hands-on experience modeling SaaS, CRM, and ERP source systems such as Salesforce or NetSuite, with clear understanding of how their object models translate into clean dimensional schemas.
Production-level expertise with Dataform or dbt, including materializations, incremental strategies, snapshots, and macros.
Strong communication skills with both technical and non-technical stakeholders, with ability to clarify needs and surface tradeoffs.
Security and compliance mindset, treating GDPR, SOX, and data access controls as integral to the role.
Fluency in English as a working language.

What makes this role worth considering

You will own canonical data models that leadership depends on, with genuine autonomy to design them properly and influence team standards. The Data Office operates with a modern, well-maintained stack including Dataform, BigQuery, Looker, and GitHub Actions, with active investment in developer experience. Your work directly powers conversations with senior leadership across finance, go-to-market, and product functions, creating immediate visibility into business impact.