Senior Analytics Engineer

Lightspeed's Data Office is hiring a  Senior Analytics Engineer  to design and own the data models that drive decisions across financial performance, GTM activities, and product insights. You'll partner with stakeholders across Finance, Revenue Ops, Marketing, and Product to deliver the analytics foundation the business runs on.

If you are someone who enjoys building data pipelines that power real business decisions and want to design canonical models that unify fragmented source systems across multiple CRMs, ERPs, and product platforms, then this role is for you. You can sit down with Finance to talk revenue recognition or with Product to map activation funnels, and walk away with a clear data model in your head.

You hold a high bar on quality, push back constructively when it matters, and don't wait to be handed a well-defined problem. You scope the work, drive it to completion, and bring others along.

What you’ll be responsible for:

Design and build the data models that power the business: financial reporting (GTV, MRR, revenue recognition), GTM analytics, and product and operational insights

Design for scale and maintainability while staying pragmatic, shipping incremental value, gathering feedback, and iterating as you go

Turn ambiguous business requirements from Finance, Revenue Ops, Marketing, and Product teams into well-scoped technical solutions with effort estimates

Collaborate across our Hub & Spoke architecture, partnering with upstream data owner teams, downstream Looker/LookML developers, and other domain pods (Retail, Hospo, Operations) to design models that work end-to-end

Treat documentation as a first-class deliverable: column descriptions, model contracts, and architectural notes that power both human reviewers and AI/LLM-assisted workflows

Diagnose root problems, not symptoms, and drive systemic fixes rather than one-off patches

Own pipeline health end-to-end: monitor proactively, lead incident response, and surface risks before they become delivery problems

Autonomously manage personal sprint commitments and contribute to team-level planning, including task breakdown, effort estimation, and priority sequencing

Mentor junior engineers through coaching, code reviews, and technical sessions, and set the bar for what good looks like

What you will bring to the team:

Expert-level SQL: query performance, clean, maintainable code, and advanced analytical techniques (e.g. window functions)

Proven experience designing enterprise-grade dimensional models on modern cloud data warehouses such as Big Query or Snowflake, including partitioning, incremental patterns, and performance optimization

Hands-on experience modelling SaaS / CRM / ERP source systems such as Salesforce or Net Suite, with a clear understanding of how their object models translate into clean dimensional schemas

Proven Dataform or dbt expertise in production: materializations, incremental strategies, snapshots, and macros

You communicate effectively with technical and non-technical stakeholders, clarifying needs, surfacing tradeoffs, and driving alignment

A security and compliance mindset: GDPR, SOX, and data access controls are part of the job, not an afterthought

Some additional things that would be a bonus :

CI/CD experience (e.g. Git Hub Actions): automated testing, linting, and deployment workflows

Python or JavaScript for data engineering tooling

LookML or equivalent semantic layer experience

Familiarity with data contracts for pipeline validation

Experience using AI/LLM-assisted tooling to accelerate development workflows: code generation, documentation, debugging, or review

Revenue/finance domain knowledge (ARR, MRR, Net Suite, revenue arrangements)

What’s in it for you:

Real ownership: you'll own canonical data models that…