Data Engineering Lead

What We Do Ascend is transforming the $10T global insurance industry by combining AI automation with embedded fintech. While insurance represents 7.2% of global GDP, outdated financial infrastructure like PDFs, emails, and manual reconciliation continues to slow the industry down. Ascend is the first and market-leading finance automation platform built specifically for insurance, driving the industry’s rapid digital transformation. In just five years: Trusted by thousands of insurance businesses nationwide Processes billions in transactions annually, growing 200%+ YoY Built a world-class team of 70+ across San Francisco and Columbus How We Do It Ascend automates the insurance financial lifecycle, from collections to disbursements. We streamline operations and drive real profitability. AI is rapidly driving the cost of software down, opening the door to faster innovation and broader access. At the same time, it is shifting where value is created. The strongest companies embed directly into financial workflows, capturing value at the point where money moves. Ascend brings AI and fintech together to automate financial operations inside the transaction itself. Customers do not just adopt software. They unlock powerful financial efficiency with a proven 5-7x return on investment. Why We Do It Insurance is a $10T+ industry running on legacy systems. AI alone won’t fix it, but AI-powered automation embedded into payments and transactions will. Ascend’s mission is to become the leading financial automation platform for insurance by 2030—powering the entire industry’s financial operations while transforming the way trillions of dollars move. Your role We are hiring a technically rigorous, systems minded Data Engineering Lead to architect and own the data infrastructure that powers decision making across Ascend. Reporting to the Head of Finance Data, this role is responsible for the full lifecycle of our data platform, from ingestion of raw, high-volume transactional data to the modeling and orchestration layers that define our most critical business metrics. You are not building dashboards for the sake of dashboards. You are building trusted, scalable data products that allow Ascend to move billions of dollars with confidence as we scale. Responsibilities will include Objective #1: In your first 30 days, you will: Develop a deep understanding of Ascend’s data sources, existing pipelines, and downstream use cases across Finance, Product, and Engineering Build strong working relationships with key stakeholders to understand current pain points, risk areas, and future data needs Evaluate the current data stack and workflows, identifying gaps in reliability, observability, and scalability Begin defining the architectural vision and technical standards for a modern, high-integrity data platform Objective #2: In your first 60 days, you will: Design and begin implementing core components of the Modern Data Stack, including ingestion, transformation, and orchestration Establish data modeling standards using dbt, with clear, version-controlled definitions for core financial and operational metrics Introduce foundational data quality and observability frameworks, including automated testing for freshness, schema evolution, and reconciliation Partner closely with Product Engineering to improve production data exports and ensure analytics infrastructure scales alongside product development Objective #3: In your first 90 days, and beyond, you will: Own and operate a trusted Single Source of Truth that defines Ascend’s core KPIs at the infrastructure level Run scalable, production-grade data pipelines that support high-volume financial transactions with accuracy and auditability Act as the technical authority on data architecture and tooling, evaluating and evolving orchestration, governance, and reverse ETL solutions Mentor future data hires and establish best practices across data modeling, CI/CD, documentation, and ... (truncated, view full listing at source)