Sr Data Engineer

Wealth.com is the industry's leading estate planning platform, empowering more than 1,000 wealth management firms to modernize the delivery of estate planning guidance to their clients. As the only tech-led, end-to-end platform built specifically for financial institutions, Wealth.com enables firms to drive scale, efficiency, and measurable client impact. Trusted by some of the largest names in finance, Wealth.com combines proprietary AI, robust security, and deep technological and legal expertise to serve the full range of client needs, from foundational plans to the most sophisticated estate strategies. The company has been widely recognized for innovation and leadership, winning Top Estate Planning Technology and Top Estate Planning Implementation at the 2025 WealthManagement.com Industry Awards, being named the 2024 Best Technology Provider in the Trust category, and earning #1 in estate planning market share in the 2025 Kitces AdvisorTech Study.

Our team is fundamental to our standing as the leading estate planning platform. We cultivate a collaborative and supportive environment, fostering innovation and making Wealth.com a truly enjoyable workplace. Wealth.com is proud to be certified as a Great Place to Work for 2025.

Every number at Wealth.com, from product usage to finance reporting to what we show our executive team, runs through our data platform. We're hiring the first dedicated Senior Data Engineer to own it.

This is a true ownership role. You'll take responsibility for our AWS data infrastructure, our dbt project, our Redshift warehouse, and the pipelines and Airflow environment that connect them. You won't inherit a mature, fully staffed function. You'll help decide what good looks like and then build it.

You'll join a team of analysts and engineers who rely on this platform every day, and you'll work closely with our Platform engineers so that when product data models change, the data platform is ready for it. Your stakeholders are mostly internal, so you'll see the impact of your work quickly and hear about it directly.

• The data platform end to end. Our pipelines, Airflow environment, dbt, and Redshift warehouse are yours to design, operate, and improve.

• Reliability and trust in the data. When a pipeline breaks or a number looks wrong, you're the person who finds the cause and makes sure it doesn't happen again.

• The path from messy source to clean warehouse. You'll bring data in from many sources, clean it, model it, and make it easy for others to use.

• Our data architecture decisions. You'll weigh in on warehouse design, scalability, and cost, and write down why we chose what we chose.

• The bridge with Platform. You'll stay ahead of upstream data model changes and make sure data and analytics have a voice in major engineering decisions.

• First 30 days: Get to know our stack, our stakeholders, and where the data platform is today. Ship something small and real.

• First 90 days: Take on day-to-day ownership of pipelines and dbt, and be the person people go to with data infrastructure questions.

• First year: Leave the platform more reliable, better documented, and easier to build on than you found it, with a clear direction for where it goes next.

• What the work looks like: A mix of building new pipelines, hardening existing ones, and partnering with stakeholders to turn a business question into a system that answers it. We're in the middle of moving onto Airflow, so you'll help carry that through.

• What the team is like: Small, collaborative, and low on process. Your priorities will come from the business, not a ticket queue, and you're expected to drive your own work.

You're a data engineer who likes owning the whole problem. You've worked on small teams where you ended up responsible for many pieces of the stack, and ideally you've also seen what a well-run data organization looks like at a more mature, scaled company. You write real Python and real SQL, and you care about whether the thing you built is still working next month.

• 4+ years in data engineering, analytics engineering, or a closely related role, including at least 2 years at a company operating at meaningful scale

• Strong SQL and Python, with Python used for data processing and pipeline work

• Hands-on experience with dbt and with orchestrating production pipelines (Airflow or similar)

• Working knowledge of AWS and a cloud data warehouse (we use Redshift)

• Good instincts for warehouse and system design

• The ability to turn a stakeholder's requirements into code and systems, and to explain your decisions clearly

• Experience moving pipelines onto Airflow or a similar orchestrator

• Experience in fintech, wealth management, or other regulated environments (compliance, audit, PII handling)

• Experience with document processing or AI/ML data pipelines