Head of Data Engineering

TRANZACT is a leading direct-to-consumer insurance services business, specializing in the distribution of Medicare Advantage, Medicare Supplement and Life & Supplemental insurance policies. Our focus is on leveraging our highly skilled team of over 3,000 professionals to deliver innovative solutions for our insurance carrier partners and provide consumers with a best-in-class experience. We work with some of America's largest insurance brands to attract, educate and connect with consumers. Our diverse team of analysts, writers, engineers, designers, business leads, data scientists and sales professionals all work together to create thoughtful, data-driven and effective marketing, technology, sales and servicing strategies. These efforts have resulted in TRANZACT earning recognition and winning awards from some of the biggest names in the industry. When you become part of TRANZACT, you join a team of passionate people who push for excellence, follow through on commitments, and love to succeed together. Our culture rests on a simple principle – “Be Real” – that means being genuine, keeping your word, and having the courage to make tough decisions. Our “Be Real” values resonate and are meaningful to us. We are entrepreneurial, fast paced and empower our people. We know how to make things happen and know that our people are always the source of our success. 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. 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. What You'll Own (Systems-Level Outcomes) 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. Key Responsibilities 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. Success Profile (6–12 Months) The data platform reliably supports key production use cases with clear SLOs, runbooks, and cost visibility. An AI-first engineering practice is established, with reusable templates and golden paths measurably increasing delivery velocity across teams. Data governance and data security controls are standardized, auditable, and enforced across the platform. Teams are staffed, aligned, and performing, with healthy delivery and quality signals. At least one critical data initiative is led to launch with documented business impact and a retrospective feeding the platform roadmap. Minimum 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. Preferred Qualifications 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. How We Work AI-first: we use AI to accelerate engineering while protecting proprietary data and process IP. Agile and iterative: prove value quickly, then scale with governance and reliability. Responsible by default: governance, lineage, permissions, security, and continuous evaluation built in from the start. Compensation and Benefits Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that base salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation. Compensation The base salary compensation being offered for this role is $200,000 USD per year. This role is also eligible to participate in the annual bonus program. Company Benefits TRANZACT provides a competitive benefit package which includes the following (eligibility requirements apply): Health and Welfare 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 and Work/Life Resources (including Employee Assistance Program) Leave Benefits: 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) Retirement Benefits: Savings Plan with annual nonelective company contribution.