Head of Data Engineering

About the role

We are hiring a hands-on data engineering leader to lead and scale TRANZACT's data engineering teams and pioneer a new AI-first data engineering discipline—accelerating the velocity, quality, and business impact of everything we build on data.

Responsibilities

• Arcitect scalable, reliable data pipelines and platform services on Databricks and PostgreSQL, supporting batch and streaming workloads across marketing, sales, and servicing domains.
• Define and roll out an AI-first engineering workflow—leveraging AI coding assistants, agentic tooling, and automated eval/QA gates—to accelerate data engineering outcomes without compromising quality or security.
• Establish data governance standards: Unity Catalog (or equivalent), lineage, data contracts, freshness and quality SLAs, and asset lifecycle management.
• Ownt data security posture in partnership with Security and Compliance: role-based access, audit trails, encryption, PII handling, and regulatory alignment appropriate to insurance data.
• Own data security posture in partnership with Security and Compliance: role-based access, audit trails, encryption, PII handling, and regulatory alignment appropriate to insurance data.
• Set engineering standards and review designs, PRs, data models, and architecture; drive adoption through documentation and enablement.
• Lead vendor and tooling evaluation, and make build/buy/insource recommendations aligned to unit economics, reliability, and IP strategy.
• Recruit, mentor, and develop engineers; host tech talks and cultivate a culture of ownership, experimentation, and continuous improvement.
• Serve as the accountable leader for critical data initiatives, driving requirements → architecture → implementation → launch → post-launch learning.

Qualifications

• 10+ years in data engineering or related distributed systems; 4+ years leading and building data engineering teams.
• Proven, hands-on experience leveraging AI to accelerate data engineering outcomes (e.g., AI coding assistants, agentic tooling, LLM-assisted pipeline development, testing, or operations).
• Deep expertise with Databricks or equivalent (Lakehouse, Delta Lake, Spark, Unity Catalog) and PostgreSQL in production.
• Demonstrated ownership of data governance and data security programs: cataloging, lineage, access control, data quality, and PII handling.
• Strong engineering fundamentals in Python and SQL; experience designing scalable ETL/ELT and streaming architectures.
• Track record of setting technical standards and delivering complex data initiatives from architecture through launch.
• Excellent communicator and mentor, effective with stakeholders across technical and non-technical domains.
• Bachelor's degree in Computer Science or related field required.