Founding Analytics Engineer
About The Position
Aboon is seeking a senior analytics engineer to own the data layer of their AI-native retirement servicing platform. This individual will be the first dedicated data hire and will have end-to-end ownership of the transformation, semantic, and AI-access layers. The role involves building and maintaining models and metrics to answer key business questions across product funnel, revenue, servicing operations, and the unit economics of AI-delivered plan administration. Additionally, the analytics engineer will help architect access patterns and the semantic layer for both human and AI agent data utilization. The company uses managed ETL (Estuary and Fivetran) for ingestion, focusing the role on downstream processes like modeling, semantics, governance, and access. The data function operates alongside product teams on a Shape Up-inspired cadence, with the analytics engineer serving as the technical SME for all data-related matters. The work produced will be the shared source of truth for engineering, servicing, GTM, and leadership.
Requirements
- 5+ years in analytics/data engineering or an engineering/analyst hybrid role.
- An expert with dbt or similar data-modeling infrastructure.
- Proficient maintaining and working within a BI tool (we use Metabase).
- Proficient working with coding agents; we’re not hand-rolling SQL or dbt models.
- Experience developing a semantic layer (dbt Semantic Layer, Cube, or similar).
- Experience making data accessible to AI — MCP servers, LLM data access, or other similar patterns.
- Skilled and familiar working within product analytics tooling (PostHog, Amplitude, or similar).
- Working understanding of how a cloud data warehouse operates (we use Redshift).
- Excellent communication skills and comfortable working with non-technical stakeholders directly.
- An instinct for governance and trust — clear metric definitions, documented lineage, and making data open and accessible across the organization.
Nice To Haves
- Experience in financial services or fintech.
- Experience working with LLM/agent observability data and eval metrics (Langfuse or similar).
Responsibilities
- Own our dbt repo, help us turn legacy queries into models, and build out the marts that power tracking and reporting of our company metrics.
- Build and govern the semantic layer and MCP connectors that let internal teams and AI agents query the warehouse conversationally and safely.
- Coordinate our data dictionary and drive org-wide data access: definitions, lineage, and self-serve analytics so every team can answer their own questions.
- Maintain and extend our product analytics taxonomy and dashboards, keeping event data trustworthy across every product line.
- Help us model the entire business: lifecycle speed, funnel conversion, revenue, and the unit economics of AI-delivered plan administration.
- Partner with engineering on warehouse architecture and data contracts.
- Be the person the company asks first when a number matters.
Benefits
- Comprehensive health, dental, and vision insurance, with additional optional coverage
- 401(k) with company match
- Flexible paid time off and holidays
- 10 weeks paid parental leave
- A fully remote work environment, with all the technology and equipment you need
- Support for professional development and career growth
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
