Finance Transformation Lead

Finance Transformation Lead Atlanta, GA Job Details Full-time 19 hours ago Qualifications Financial forecasting 7 years Internal controls Data transformation pipeline development Cloud data warehouses Automation Data migration Technical documentation Financial reporting R Scalable systems Snowflake SQL Data quality monitoring Prototype creation Data analytics Scalability Financial regulatory compliance Senior level AI Project leadership Prototypes Project stakeholder communication Python Cross-functional communication Stakeholder management Database software proficiency Full Job Description

OVERALL RESPONSIBILITIES

The Finance Data Transformation Lead is responsible for designing, building, and maintaining finance and actuarial data pipelines and data foundations that support financial reporting, analytics, and decision making. This role serves as the primary liaison between Actuaries, Finance, and IT to ensure data is accurate, well governed, auditable, and fit for regulatory and business needs. The role leads finance data modernization efforts, reduces reliance on manual processes, and ensures data solutions support long term scalability, control integrity, and advanced analytics.

SPECIFIC DUTIES

Design, build, and maintain finance data pipelines and transformations, with Snowflake as the primary enterprise data repository. Actively support and execute components of the migration from Oracle-based finance data to Snowflake, improving structure, performance, and accessibility. Build reusable, well-documented data assets that materially reduce reliance on manual spreadsheets and one-off extracts. Serve as the finance-side technical owner for data modernization initiatives, working closely with IT and enterprise data teams. Determine, on a use-case-by-use-case basis, whether the work is best delivered through direct development or through managed project execution. When acting as a project lead, define clear data requirements, success criteria, and acceptance standards—while remaining technically close enough to validate solutions. Ensure that all solutions are designed for long-term scalability, auditability, and AI enablement rather than short-term reporting fixes. Drive upstream data governance by serving as the liaison between finance end users and the business processes and systems that generate source data. Partner with underwriting, operations, investments, and other upstream functions to improve data consistency, definitions, and process discipline at the point of origin. Establish and reinforce clear finance data definitions, ownership, and usage standards in collaboration with IT and data governance teams. Identify where finance data issues are rooted in business processes—not just systems—and help drive remediation. Build finance data foundations that support advanced analytics, forecasting, scenario modeling, and AI-driven operational workflows. Partner with finance SMEs and data scientists to ensure AI and automation efforts are grounded in trusted, well-structured data. Rapidly prototype data-driven solutions to demonstrate value, then harden and scale them as appropriate. Work directly with accountants, actuaries, and investment professionals to understand how data is actually used in practice. Embed in finance workflows to ensure data solutions materially improve speed, accuracy, and insight—not just technical elegance. Ensure that finance data solutions meet regulatory, audit, and internal control expectations. Build data quality checks, lineage, and documentation into day-to-day development and project work. Ensure modernization strengthens financial controls while increasing efficiency and transparency.

QUALIFICATIONS, EXPERIENCE REQUIRED

7+ years of relevant experience required Advanced SQL skills, including complex transformations and performance optimization across large datasets. Strong working knowledge of Python and/or R for data transformation, analytics, and automation. Hands-on experience with modern cloud data platforms; Snowflake experience is strongly preferred. Strong understanding of analytical and finance-oriented data modeling concepts. Demonstrated ability to automate manual, spreadsheet-heavy processes. Deep understanding of finance, actuarial, investment, or insurance data and how it supports reporting and decision-making. Ability to balance technical design choices with accounting, regulatory, and control considerations. Experience working closely with senior finance stakeholders on complex, high-impact initiatives. Clear communicator who can bridge finance, data, and IT without losing accountability.

Location:

Atlanta Office