Senior Analytics Engineer

LawVu is the AI-native operating system for in-house legal - the foundational layer that powers the entire legal function. Our intelligent platform connects legal intake, matters, contracts, spend, and reporting in one connected workspace, enabling legal teams to work smarter, move faster, and deliver measurable business value.

Trusted by leading organizations including Discord, Employment Hero, Etsy, and many more, LawVu is helping legal teams transform from reactive service providers into strategic business partners.

Founded in New Zealand, LawVu is a fast-growing global software company with customers and employees across North America, Europe, Australia, and New Zealand. Backed by leading venture capital firms, including Insight Partners and Airtree Ventures, we're creating a new category of LegalOS software purpose-built for modern in-house legal teams.

About the role

Are you ready to turn raw data into decisions that shape the future of legal tech? As a Senior Analytics Engineer, you'll own the full journey from a stakeholder's question to a trusted, production-ready data product — working across Databricks and Power BI to shape how data is modeled, governed, and delivered across our Legal OS platform.

What you’ll do

End-to-End Ownership

· Take a request from a stakeholder conversation all the way through to a deployed, working data product.

· Own the accuracy andreliability of the data products you ship, not just the initial build

· Anticipate downstream impacts of your work and proactively flag risks or blockers before they become problems.

· Follow through on maintenance and iteration — data products aren't "done" at launch, and you stay accountable for how they perform over time.

Design & Data Modeling

· Think through the right data model and structure before building, not just after.

· Build and shape data models across Databricks and Power BI to support reporting and analytics.

· Design for reusability and scalability, so data products can extend to new use cases without significant rework.

· Maintain clear documentation of data models, transformations, and lineage so others can understand and build on your work.

· Consider performance implications of design choices, optimizing models and queries for both usability and efficiency

Stakeholder & Customer Engagement

· Translate a Product ask or an internal business question into a clear, actionable spec.

· Clearly articulate technical concepts to both technical and non-technical stakeholders.

· Write data specifications and gather requirements directly with customers, product managers, and internal business users.

· Translate technical concepts, risks, and technology recommendations for non-technical users, balancing business needs with technical reality.

Data Quality & Governance

· Care as much about data accuracy and test coverage as about shipping fast.

· Build and maintain automated data tests.

· Apply data governance practices — classification, tagging, and maintaining a data dictionary.

Collaboration & Delivery

· Partner with Product, Design and Engineering leadership on roadmap planning, backlog refinement, and estimates — resolving blockers and keeping delivery risk visible early.

· Collaborate with Data Engineers and Software Engineers on upstream pipeline and platform work.

· Work within an Agile environment, contributing to sprint planning and delivery.

Skills and Experience

· 5+ years experience in data and analytics

· Strong exposure to Azure, Databricks and Power BI.

· Solid understand of modern data lake architectures.

· Advanced SQL, Python and experience with data modeling/transformation.

· Experience with GitHub, including CI/CD pipelines and modern engineering workflows.

· Experience writing data specifications, gathering requirements, and collaborating directly with stakeholders (customers, product managers, internal business users) to build data products.

· Building and maintaining automated da