• Deploy & Lead dbt Implementation: Act as the internal champion for dbt. • Architect the Single Source of Truth: Define the core data models that align the entire company. • Fuel AI & Self-Service: Design the Gold Standard tables that will serve as the brain for our Self-Service Platform and AI Assistants. • Build for History: Use dbt’s snapshotting and modeling capabilities to implement historical tracking (SCDs). • Pipeline Optimization: Collaborate with Data Engineering team to optimize AWS Airflow DAGs.

• Deploy & Lead dbt Implementation: Act as the internal champion for dbt. • Architect the Single Source of Truth: Define the core data models that align the entire company. • Fuel AI & Self-Service: Design the Gold Standard tables that will serve as the brain for our Self-Service Platform and AI Assistants. • Build for History: Use dbt’s snapshotting and modeling capabilities to implement historical tracking (SCDs). • Pipeline Optimization: Collaborate with Data Engineering team to optimize AWS Airflow DAGs.

Your opportunity Our client builds North America’s leading clinical practice software for mental healthcare providers. They are a mission-driven innovator rooted in research and building the tools to support the emergent clinical category they are creating. They currently serve >350 healthcare organizations and tens of thousands of clinicians delivering care in clinics, hospitals, campuses and workplaces. The company also serves regional health systems by providing population-level insights and bolsters continuity of care by making patient data on the platform portable to a variety of care providers and program administrators. The mission was inspired by personal experiences with the shortcomings and inconsistencies in mental healthcare practice and the founders are dedicated to improving the quality of care within these systems. The company is ~9 years old and recently closed its first lettered venture round of financing. Despite the capital injection the team is growing in line with revenue, and minimal reliance on outside capital. The current wave of hiring was unlocked by revenue and a large implementation that will roll out to millions of insurance plan members over the coming months. The company is ~80 total team members and as a analytics engineer, you will join an R&D organization of ~29 team members (with a data team of~5, ~7 in product and design, and ~17 in software engineering). The teams are organized into 5 cross-functional pods focusing on platform, core clinical solutions, data and AI platform, integrations, and population health. The data team that you will join works with highly privileged data and produce insights that meaningfully improve people’s health. They are a small, growing, remote-first team and successful data team members tend to be high ownership communicators who take initiative, clarify requirements, and work cross-functionally with a steady eye on high-level business requirements and constraints. Key responsibilities - Data modelling & transformations: Own and evolve the analytics data model in dbt/BigQuery, building maintainable, well-tested transformations that support product analytics, custom use cases, and new feature development - Looker stewardship and analytics technical strategy: Act as a technical steward for Looker and help shape the broader analytics strategy, including explores, views, folder structure, customization patterns, performance, and developer workflows - Customer analytics customizations: Own the technical delivery of complex customer-specific analytics requests, from scoping and prioritization through implementation, testing, documentation, rollout, and customer walkthroughs - Analytics architecture and productization: Default to reusable, productized solutions wherever possible, creating shared models, standard tiles, and scalable patterns to minimize one-off work - Analytics support, debugging, and reliability: Serve as a senior escalation point for analytics issues, investigating metric discrepancies, broken dashboards, performance regressions, and recurring problems while improving SLAs, monitoring, and long-term stability - Cross-functional collaboration: Partner closely with the product, design, success, and support teams to translate requirements into analytics solutions and bring customer insight into roadmap and product decisions - Documentation, enablement, and continuous improvement: Strengthen team effectiveness through clear documentation, internal enablement, and a steady focus on maintainability, backward compatibility, and modern analytics engineering best practices Your know-how - You have 3+ years of experience owning data modelling and BI tooling as a data analyst, analytics engineer, BI engineer or data scientist - You are experienced with SQL, Python and modern data warehousing - You care deeply about clean and efficient models, tests and documentation and are experienced with dbt or a similar transformation framework - You have experience building views, dashboards and self-service data exploration with Looker or a similar BI tool - You have experience gathering requirements directly from customers and other internal and external stakeholders - You are comfortable owning the reliability of analytics systems in production and have experience investigating incidents, shipping fixes and designing solutions that proactively mitigate outages - You think in AI-first terms, actively adopt and integrate AI tools in your own workflow to accelerate your work - You are a pragmatic person with experience making tradeoffs between shipping a solution quickly and investing in more robust solves - You have an excellent command of English and are comfortable adapting your communication style for non-technical audiences - You have a contagious growth mindset and persistently seek opportunities to improve yourself, the team, products and processes in a scaling business It’s a bonus if - You have experience working on enterprise-grade software that handles sensitive data - You have previously served in a business that faces healthcare or other regulated industries - You have experience building or scaling a B2B or B2B2C venture - You have an acute interest in mental healthcare or health technology Interested in learning more? Please apply using the following form or send your resume or LinkedIn profile URL to talent@lutrapartners.com with “Analytics Engineer, Mental Healthcare” as the subject line. One of our talent partners will be in contact shortly.

• As a Senior Analytics Engineer within our team, you will lead initiatives on topics such as data quality, observability and model optimisation. Typical responsibilities could involve; • Design, build and maintain high quality datasets for engineers to build robust customer facing reporting • Collaborate closely with engineers to assess and mitigate the impact of upstream product changes • Apply domain knowledge to develop semantic layers for business intelligence • Develop data models optimized for efficient querying over large datasets, specifically for reports embedded within our main platform