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

Role Description As Analytics Engineer, you will support the Senior Analytics Engineers in one or more of the many functional data domains within JUMO. Working closely with various stakeholders and Data engineers to service data requests both internally and to external partners. You will report to the Data Modelling & Reporting Team Lead. You will: - Work closely with all stakeholders including technology platform Product Owners, Data & Prediction teams, Finance, Marketing, and external partners to perform investigations on data warehouse and other operational data stores. - Understand the end-to-end architecture of your functional domain and deep dive into the data to resolve issues or perform ad-hoc extracts. - Perform quality assurance on new and existing data sets and pipelines to discover inconsistencies and anomalies to guide problem resolution and data cleansing exercises. - Use advanced data query and discovery skills for ad hoc analysis and support for both internal and external stakeholders. - Clearly define reporting requirements and build operational reports and strategic dashboards. Qualifications - 3-5 years experience with data and/or systems analysis experience, at least some within a formal BI environment. - University degree in Business, Finance, Mathematics, Statistics, Informatics, or equivalent industry training and experience. - Proven ability in analytics, business process analysis, and presenting/communicating recommendations across all organization levels. - Real-world understanding of data processing and storage. - Relational database management systems experience in relevant technologies such as MySQL, PostgreSQL, Redshift, and SQL Server. - Proven ability to write complex data queries (in any desired language) to retrieve data for analysis, modeling, and solving complex business scenarios. - Ability to self-discover and understand complex data domains. - Advanced Excel skills. - Understanding of Data Governance, Agile methodologies, and QA standards. - Critical thinking under pressure with ambiguity and tight deadlines. - Experience working with Github and JIRA or similar task or project management tools. Requirements - Experience in data environments making use of big data, data lakes, event-based streaming, and API integrations. - Experience with reporting and business intelligence software such as Tableau, Power BI, Grafana, Superset. - Experience with tools such as Airflow and NiFi. - Experience with end-to-end BI solution design and build. - Experience in the FinTech industry. Benefits - Collaborating with smart, engaging people in an inspiring work environment. - Working as one team towards our goal of financial inclusion. - Growing and learning continuously, with loads of encouragement and support. - Boldly taking risks as we navigate new challenges. - Flexible work practices enabling your best delivery. - Being autonomous and empowered to lead. - Using AI for good, ensuring more value for more customers. - A stack of leading-edge technologies. - Remote First working approach. Company Description This position is based in South Africa. We operate a remote first working approach, where working remotely is our default way of working. Our environment is designed to foster innovation and enable collaboration. We have co-working spaces available in Cape Town for collaboration and connection for those who value and want to work out of an office. You have flexibility where to work from, as long as you are set up to work remotely and have access to data with a strong and reliable connection as we value online facetime for collaboration at JUMO. At JUMO, we firmly believe that diversity strengthens our teams. We are dedicated to fostering an inclusive recruitment process that cultivates an environment where all individuals can be authentic, collaborate, and thrive.

• Develop and prototype cloud‑native analytics solutions using Power BI (Desktop, Service), DAX, Power Query (M), dataflows, deployment pipelines, and Snowflake components including schemas, virtual warehouses, roles, tasks/streams, and performance services. • Lead full‑cycle development (SDLC + agile) of secure, scalable, and cost‑efficient analytics, including design, build, test, documentation, and support. • Implement governance controls including row‑level and object‑level security, data endorsements, versioning, and reliable refresh pipelines. • Perform source‑to‑target mapping and design star/snowflake models optimized for analytics and semantic modeling. • Build semantic layers and governed calculation frameworks (DAX measures, calculation groups). • Optimize model and query performance using aggregations, incremental refresh, model size tuning, and Snowflake performance strategies (clustering, caching). • Write medium to complex SQL queries for data validation, quality checks, and in-depth analysis. • Operationalize production pipelines, schedules, workflows, alerting/monitoring, and SLAs. • Provide Level 3 support (ServiceNow), including triage, root‑cause analysis, and stable release management. • Partner with business and technical stakeholders to define requirements, lead design workshops, and produce actionable prototypes and wireframes. • Design high‑value dashboards, reports, and analytics that provide product insights and operational decision support. • Own end‑to‑end design for visualization, reporting, and dashboard solutions that power product insights and operational decision‑making. • Communicate proactively with teams and stakeholders; escalate risks early to ensure on‑time delivery. • Champion quality, standards, and continuous improvement through architecture/code reviews, operational documentation, and usage/cost awareness across workloads. • Research emerging cloud analytics capabilities and ensure compliance with required training and SOPs (e.g., GCP, 21 CFR Part 11, CAPA). • Explore new opportunities to add value through automation, standardization, and measurement. • Support teammates to achieve shared outcomes; perform other duties as assigned. • Maintain version-controlled BI assets using GitLab (commit, push, merge requests, resolving conflicts) • Use Jira for sprint planning, task updates, story tracking, and collaboration within Agile teams. • Collaborate with data engineering teams to ensure accurate and consistent data flows. • Support root-cause analysis for data discrepancies reported by business users. • Participate in patch releases, including validation, deployment coordination, and documentation • Maintain strong, current knowledge of cloud analytics, Power BI, Snowflake, data engineering patterns (ELT/ETL), data governance, and security.