Founding Analytics Engineer

Aboon; United States; Remote; USD 170,000 - 190,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

401(k) with company match

Flexible paid time off and holidays

10 weeks paid parental leave

Fully remote work environment

Professional development support

Job summary

Aboon is seeking a senior analytics engineer to own the data layer of our AI-native retirement servicing platform. You’ll be our first dedicated data hire, with end-to-end ownership of transformation, semantic, and AI-access layers.

You’ll build models and metrics across product funnel, revenue, servicing operations, and the unit economics of AI-delivered plan administration. You’ll help architect access patterns for humans and AI, joining a small, flat team.

Qualifications

• 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.

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.

Skills

Analytics/Data Eng

dbt / Data Modeling

Metabase

AI Data Access

Semantic Layer

Product Analytics

Redshift

Communication

Data Governance

Fintech

Langfuse/Observability

Tools

PostHog

Amplitide

Job description

About Aboon

Setting up a 401(k) shouldn't be the hardest thing a business ever does. But retirement plan administration is complex, fragmented, and manual, and it slows down both business owners and the financial advisors who serve them. Aboon was founded to change that.

We're an AI-native platform and third-party administrator that makes it easy for financial advisors to find, win, and grow 401(k)s and other retirement products by pairing streamlined workflows with dedicated human service. Backed by leading investors including Bain Capital and Edward Jones Ventures, we bring decades of experience building for advisors and the retirement industry. We're looking for exceptional, mission-driven people to build it with us.

About the role

We're seeking a senior analytics engineer to own the data layer of our AI-native retirement servicing platform. You'll be our first dedicated data hire, with end-to-end ownership of the transformation, semantic, and AI-access layers.

You’ll be responsible for building and maintaining the models and metrics that answer our most important questions across our product funnel, revenue, servicing operations, and unit economics of AI-delivered plan administration. Just as important, you’ll help us architect the access patterns and semantic layer that enable both our humans and AI agents to leverage our data in our day-to-day operation.

We use managed ETL (Estuary and Fivetran) and zero-ETL for ingestion, so you won't be building bespoke pipelines. Your job is everything downstream: modeling, semantics, governance, and access. You'll join a small, tight-knit team in a flat hierarchy. Our product teams run a Shape Up-inspired cadence; the data function operates alongside it, and you'll serve as the technical SME and go-to resource for all things data across those teams.

Your work will be the shared source of truth for engineering, servicing, GTM, and leadership.

What you’ll do

• 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.

Our stack

• Redshift + dbt + Metabase.

• PostHog for product analytics.

• Langfuse for agent traces and evals.

• Asana, Stripe, HubSpot, Customer.io as source systems.

• Rails/PostgreSQL, zero-ETL to warehouse.

• Estuary/Fivetran for ETL

What you bring

Required

• 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 have

• Experience in financial services or fintech.

• Experience working with LLM/agent observability data and eval metrics (Langfuse or similar).

What we offer

Compensation

The base salary range for this role is $170,000–$190,000, depending on experience, skills, and location. Total compensation also includes an annual bonus and equity.

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

Location

Remote, though we encourage in-person attendance at 1-2 company retreats per year. This role is open to candidates based in the US. Work authorization required; no visa sponsorship.

Aboon is an Equal Opportunity Employer. We encourage applications from all qualified individuals and do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected status.