Job Summary:Frazier & Deeter is seeking a
Senior Data Engineer to help build and scale the data foundation that powers our firm's technology, automation, reporting, and AI initiatives. In this highly visible role, you will design and optimize enterprise data solutions that support business decision-making, operational excellence, and strategic growth. Working closely with technology and business leaders, you will play a key role in ensuring data is trusted, accessible, secure, and positioned to drive innovation across the organization.
Duties & Responsibilities:- Design, build, and maintain trusted data foundations across financial, practice-management, tax, audit, advisory, CRM, and operational systems.
- Lead data migration planning and execution during mergers and acquisitions, including mapping, validation, reconciliation, and migration of active data.
- Design approaches for historical information, including data lake or warehouse structures where historical data should be retained outside transactional platforms.
- Develop and optimize ETL/ELT pipelines, data models, data quality checks, and integrations that support reporting, automation, and AI-enabled workflows.
- Partner with Business Analysts and practice teams to understand data meaning, source-system complexity, and required downstream use.
- Collaborate with AI Enablement Engineers to make trusted data available for automations, agents, reporting, triggers, and validation routines.
- Ensure data handling aligns with security, governance, privacy, and compliance expectations.
Education & Experience: - 7+ years of hands-on data engineering experience.
- Advanced SQL, Python, ETL/ELT, data warehouse, data lake, and cloud data architecture experience.
- Proven experience leading data migrations or complex integrations across enterprise systems.
- Strong understanding of data quality, validation, reconciliation, governance, and source-of-truth design.
- Experience with Microsoft data platforms, AWS services, APIs, and integration patterns preferred.
- Ability to communicate complex data issues clearly to technical and non-technical stakeholders.
#LI - hybrid
