Senior Data Engineer

At Current, everything starts with people. We believe that when you invest in talent through opportunity, development, and support, you unlock growth for individuals, firms, and clients alike. That’s why we’ve built a platform designed to give our people access to more: more learning, more collaboration, and more ways to grow their careers than any single firm could offer on its own.

Founded in 2023, Current has rapidly become one of the fastest-growing accounting platforms in the country, partnering with more than 40 leading accounting firms across the United States. Today, our community includes over 2,000 professionals, 30+ offices nationwide, and a growing global workforce that supports clients around the world. Backed by Thrive Capital, Bessemer Venture Partners, and Springdale Industries, Current is investing heavily in technology, artificial intelligence, and workforce innovation to help modernize the profession.

Our leadership team has a proven track record of building and scaling successful businesses, with prior ventures generating more than $3 billion in combined enterprise value.

We’re building something bigger than a traditional accounting firm: a platform where talented people can grow faster, learn more, and do more meaningful work. Whether you join Current, one of our partner firms, or our global team, you’ll be part of a community shaping the future of the profession.

Current is building a scalable data platform for a growing network of accounting and advisory firms. We connect operational and financial data across firms to support faster closes, better decisions, and healthier margins.

We are looking for a hands-on Senior Data Engineer to strengthen that foundation. Your initial focus will be core dbt models and financial reconciliation: creating consistent definitions, connecting data across systems, and ensuring that reported results tie back to source records. Your work will support analytics, applications, and automation used by firm and enterprise leaders.

You will work alongside our Lead Analytics Engineer and Data Analyst, sharing architecture decisions with your manager and engineering colleagues. This is an individual-contributor role focused on data engineering and modeling, with opportunities to mentor teammates and shape engineering standards.

• Build and maintain tested, documented dbt models across bronze, silver, and gold layers, with particular emphasis on reusable business models and consistent metric definitions.

• Refine canonical models for firms, clients, employees, projects, time, work in progress (WIP), invoices, cash receipts, and revenue.

• Reconcile financial and operational data to source systems. Investigate discrepancies and build controls that make data quality measurable and exceptions actionable.

• Create entity crosswalks and historical logic that preserve reporting continuity through acquisitions, firm migrations, and changes in source systems.

• Build and improve ingestion from SQL Server, cloud databases, SaaS platforms, and APIs using Python and SQL. Design incremental, idempotent loads that protect source performance and support reliable backfills.

• Strengthen production reliability through automated tests, freshness checks, schema-change monitoring, alerts, logging, and clear operational documentation.

• Partner with engineering colleagues to implement secure access and firm-and-user-level data isolation and improve the performance and cost efficiency of Databricks and dbt workloads.

• Work with Operations, Finance, HR, and Engineering to translate business requirements into reusable data products and stable, documented data contracts.

• Contribute to Git-based development, CI/CD, code reviews, and shared engineering standards.

• Understand the existing platform and align on near-term priorities for core models, reconciliation gaps, and the data platform roadmap (today’s state and where we want to take it).

• Deliver priority dbt models with clear definitions, tests, documentation, and traceability to source data, supporting a current firm or finance need.

• Establish repeatable reconciliation checks and exception reporting for priority financial data, reducing manual investigation and increasing confidence in downstream reporting.

• 5+ years in data engineering, analytics engineering, or a related role. We also welcome candidates with equivalent depth of relevant experience.

• Advanced SQL and strong production…