Data Engineer, Finance

About DAT

DAT Freight & Analytics is an award‑winning employer of choice and a next‑generation SaaS technology company that has been at the leading edge of freight and logistics innovation for nearly five decades. Founded in 1978, DAT operates the largest freight marketplace in North America – processing 250 million+ load posts annually and maintaining one of the largest repositories of freight market transaction data in the world.

On a defined path to $1 billion in revenue, DAT deploys a suite of software solutions, machine learning models, and intelligent automation tools that help brokers, carriers, and shippers price freight accurately, source capacity, reduce risk, and operate more efficiently. With nearly 700 teammates across offices in Denver, CO;
Portland, OR;
Seattle, WA;
Springfield, MO;
Toronto, ON; and Bangalore, India, DAT combines the credibility of a multi‑decade market leader with the drive of a company that is not done disrupting the industry it helped build.

06/31/2026

We're a fast‑growing team tackling a massive opportunity: the $800B US freight market. This industry comprises 1.6 million carriers, with 95% being small businesses operating 10 or fewer trucks. These hard‑working business owners often face tight margins while being forced to rely on predatory financial products laden with exorbitant rates, hidden fees, and restrictive contracts.

At DAT Outgo, we're changing that. We're building an intelligent fintech platform from the ground up that truly understands the unique needs of trucking businesses. Our platform operates with radical transparency and fairness, optimizing cash flow to help truckers save more and grow their businesses.

Join our dynamic team at DAT in our mission to level the playing field and empower America's truckers with the financial tools they deserve.

The DAT Outgo engineering team is at the heart of revolutionizing financial services for the logistics industry. We build robust, fault‑tolerant systems that make real‑time decisions and manage money flows with bank‑grade reliability. Our technology transforms the accounts receivable process through intelligent automation and visualization, multiplying our operations team's effectiveness. For our customers, we craft intuitive, trustworthy applications that set a new standard for financial services.

Our modern data stack is built on Snowflake and DBT and powered by AWS infrastructure. We leverage cutting‑edge tools including Pulumi, Postgres, and Claude Code to deliver exceptional results.

Our seasoned engineering team brings deep experience from both successful startups and leading enterprises. We're looking for data engineers who share our passion for building impactful products that make a real difference in people's lives. Here, you'll find a culture that values:

• Technical craft and engineering excellence
• Intellectual curiosity and continuous learning
• Strong team collaboration and camaraderie
• Individual autonomy and ownership

• Partner with Finance, Accounting, and Capital Markets teams to build auditable, automated reporting systems, datasets, and visualizations
• Build and own data models that are accurate and simple, with a focus on close processes, FP&A workflows, and asset and revenue reporting
• Demonstrate pride, ownership, and accountability for your work, and expect the same from those you work with
• Share opinions openly on what's working and what's not across the product, tech stack, and team processes
• Seek feedback early and often in the development process
• Identify speed vs quality tradeoffs and balance them judiciously
• Believe diverse teams make better decisions, and actively foster a culture where every person can do their best work

• 7+ years of combined experience in Data Engineering and/or Accounting or Finance, including at least 4 years in a Data Engineering role focused on building and maintaining analytical or product datasets
• Experience with FP&A processes, close workflows, and financial reporting
• Familiarity with GAAP vs. non‑GAAP reporting and revenue recognition concepts
• Track…