Engineering Tech Lead, Migration Platform

CARET provides technology and automation solutions for legal and accounting firms through practice management, document automation, and payment processing platforms. The Engineering Tech Lead will own the end-to-end architecture of an AI-accelerated migration platform, leading the design and implementation of data extraction, transformation, orchestration, assessment, and go-live workflows.

Responsibilities:

• Own the architecture across extraction, transformation, and orchestration - the full migration pipeline
• Translate technical strategy into buildable platform increments alongside the team
• Develop deep knowledge of the CARET Legal data model and how it maps to application behavior, workflows, and customer outcomes
• Gain an in-depth understanding of legal practice management and accounting, including the workflows, customer problems, and data relationships CARET Legal solves and supports
• Design for correctness and scale, migrating legal practice data across many firms and source systems with a high bar for accuracy, traceability, and customer trust
• Build repeatable go-live patterns that make migrations faster, more predictable, and easier for customers to adopt
• Shape problems into buildable work with the technical product manager, making disciplined tradeoffs to keep delivery focused and predictable
• Apply AI thoughtfully to accelerate migration assessment, mapping, validation, and engineering workflows where it improves speed, quality, and scalability
• Lead the team and set a high technical bar, including clear documentation and handoff practices that keep the platform maintainable and easy to extend
• Be the technical point of contact for operations and migrations, aligning technical decisions with migration planning and customer delivery needs

Requirements:

• 8+ years building data-intensive backend systems, including experience leading architecture across a team
• A unique ability to reverse engineer application systems by performing forensic analysis of their underlying data structures and storage
• Deep experience building reliable data pipelines and ETL/ELT systems, including extraction, change data capture, transformation, and orchestration at scale
• Hands-on strength in a modern data stack, including SQL, a transformation framework such as dbt, and cloud orchestration such as Microsoft Fabric or Azure Data Factory
• A strong bias for correctness, observability, and traceability when data quality, lineage, and edge cases require disciplined engineering
• Ability to operate as a hands-on technical lead: setting direction, raising the engineering bar, and contributing code
• Pragmatism about scope and sequencing, with the judgment to pair a strong platform foundation with practical AI and automation where each creates durable value
• Experience leading data migration or system-to-system consolidation initiatives
• Experience with multi-tenant SaaS applications and systems
• Experience in legal, fintech, healthcare, or another domain with high standards for correctness, confidentiality, and compliance
• Experience building a new platform or team from the ground up
• Experience applying AI or LLMs responsibly to accelerate data mapping, assessment, or transformation