Data Engineering Lead

Location: San Francisco, CA

Department: Data

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 audibility
• 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 peer review
• Translate complex financial and business logic into reliable, performant data structures that enable confident decision making across the company

Base Salary: $200-230K

You might be a good fit if you are/have: 

• 6-8 years of experience
• Deep experience designing end-to-end data platforms using tools like Snowflake/BigQuery, dbt, Airflow/Dagster, and Fivetran/Airbyte.
• Strong understanding of financial data integrity, including reconciliation, ledger-based modeling, and the nuances of B2B SaaS and lending metrics.
• Passionate about CI/CD, data testing (Great Expectations/dbt tests), and building "self-healing" pipelines.
• Someone who thrives in the ambiguity of an early-stage startup and can transition seamlessly from high-level architecture to hands-on SQL and Python coding.
• Have experience working in our toolsets, which include Slack, Notion, Excel, Front, and Linear.
• Strong written and verbal communication skills, ability to quickly understand complex (and sometimes dense) subject matter, and great attention to detail