Senior Analytics Engineer

ABOUT ALEPH

Aleph is an AI-native platform for Financial Planning & Analysis (FP&A), an established software category with a multi-billion market but no clear winner. We’re trying to solve a problem many finance teams are super familiar with: data scattered across a million systems, endless spreadsheets and way too much time spent getting numbers to line up instead of actually using them to make decisions.

Aleph was founded by Albert Gozzi and Santiago Perez De Rosso, two technical founders with backgrounds from Stanford and MIT and experience working at top-tier companies such as Google, Microsoft and Bain & Company. We’re backed by top VCs (Khosla Ventures, Bain Capital Ventures, YC, Picus Capital), and work with customers like Webflow, Notion, Zapier, Y Combinator and many others.

We are hiring remotely across the Americas (United States, Canada, LATAM).

🔍 WHAT WE'RE LOOKING FOR

This is a senior analytics engineering role on Aleph's Data team. Our customers integrate diverse systems (financial data, headcount and payroll data, sales and customer data) into Aleph, and we own everything that happens next. We build and maintain the transformations that turn messy raw data into FP&A-ready analytical tables, defining one golden set of transformations across all customers while adding customization where it matters.

We're in an exciting phase of growth, scaling fast on strong foundations. The problems here span building reliable, performant transformation pipelines and data models, and integrating diverse sources at scale. We focus on data integrity, performance, and flexibility, and we lean on AI to ship faster and keep support light.

🧑‍💼 WHAT YOU'LL BE DOING

• Own how we build client-facing data transformations faster, better, and in a more scalable way as we add integrations and customers, including where and how we leverage AI to accelerate, improve, and document that work

• Design and evolve data integrity tests in collaboration with Engineering and Customer Success, so issues are caught before they reach customers

• Partner with Customer Success to understand data and reporting needs, troubleshoot issues, and build robust transformations across many sources

• Refactor and optimize critical models and pipelines, defining patterns and conventions others follow

• Raise the bar through excellent code, thoughtful reviews, and clear communication; improve team processes and developer experience

📋 WHAT YOU BRING

• Experience: A track record of owning transformation pipelines over financial or operational data end to end, from source integration through production-ready models. Experience working with financial data is a plus

• Strong fundamentals: you can reason about data from source to consumption and make good technical decisions across the pipeline. Strong SQL and experience with dbt (or similar); comfort with version control, testing, and deployment

• High agency: you drive standards, support and incentivize great practices across the team, and shape architectural decisions. You handle ambiguity without needing constant direction and are the person others trust when things are hard or unclear

• Craft: you care deeply about code quality and data integrity, building transformation layers that are reliable, performant, and well-documented, and refactoring and optimizing at scale

• Communication: clear, direct, and persuasive with technical and non-technical audiences, partnering effectively with Customer Success, Engineering, and stakeholders

• Growth trajectory: you uplevel the team, thrive in a fast-paced environment, coach others, and contribute to hiring and onboarding

🛠️ TECH STACK

You're familiar with our stack or can learn quickly:

• Transformations: dbt, SQL, Python

• Data: BigQuery

• Integrations: many sources (ERP, HRIS, CRMs, billing); ingestion includes Airbyte, Fivetran, Merge

• Observability: Datadog

• Version control & deployment: Git, CI/CD for dbt

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