Head of Data Engineering

TRANZACT•Fort Lee, NJ

17h•$200,000

About The Position

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. You will own the architecture, delivery, governance, and security of our modern data platform built on Databricks and PostgreSQL, while embedding AI into how our teams design, build, and operate data systems. This role combines strategic platform ownership with sleeves-rolled-up execution and people leadership.

Requirements

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.

Nice To Haves

Master's degree in Computer Science, Data Engineering, or a related field.
Experience in insurance, healthcare, or other regulated, data-sensitive industries.
Experience with Apache Airflow (or comparable orchestration frameworks) and SQL Server in production.
Cloud-native experience on Azure and/or AWS, with strong infrastructure-as-code practices (e.g., Terraform, Bicep, CloudFormation).
Familiarity with data observability, dataset versioning, and approval/quality gates.
Exposure to ML/AI platform enablement (feature stores, model registries) supporting data science teams.

Responsibilities

Define and evolve the end-to-end data platform strategy across ingestion, transformation, storage, and serving—anchored on Databricks (Lakehouse, Delta, Unity Catalog) and PostgreSQL—with production-grade reliability and cost efficiency.
Establish an AI-first data engineering practice: standard patterns, SDKs, and golden paths that use AI to accelerate pipeline development, testing, documentation, and operations across teams.
Stand up enterprise-grade data governance and data security: cataloging, lineage, access controls, data quality, PII handling, and policy enforcement across the platform.
Build and lead high-performing data engineering teams—hiring, mentoring, and setting the technical bar—while driving measurable improvements in delivery velocity and platform trust.
Uplift the broader Engineering and Data organizations by sharing reusable components, best practices, and self-service capabilities that reduce bottlenecks and vendor dependency.
Serve as the accountable leader for critical data initiatives, driving requirements → architecture → implementation → launch → post-launch learning.
Architect 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.
Own data security posture in partnership with Security and Compliance: role-based access, audit trails, encryption, PII/PHI 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.

Benefits

Medical (including prescription coverage)
Dental
Vision
Health Savings Account
Health Care and Dependent Care Flexible Spending Accounts
Group Accident
Group Critical Illness
Life Insurance
AD&D
Group Legal
Identify Theft Protection
Wellbeing Program
Work/Life Resources (including Employee Assistance Program)
Paid Holidays
Annual Paid Time Off (includes state/local paid leave where required)
Short-Term Disability
Long-Term Disability
Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave)
Savings Plan with annual nonelective company contribution.
Annual bonus program