Analytics Engineer, Mental Healthcare

Lutra

2d • Remote

About The Position

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.

Requirements

• 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

Nice To Haves

• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1-10 employees