This role pays less than
94%
of similar roles. Most pay
$167,850–$223,750
— the shaded band above.
At the midpoint, this role pays about
$134k
versus about
$196k
for comparable roles.
Based on 239 similar postings.
Employer
About The Hartford
The Hartford is a leading provider of property and casualty insurance, group benefits, and mutual funds, serving businesses and individuals across the United States. Industry: Insurance & Financial Services
The Hartford currently has
46 open roles
on FindRole.
Listed pay typically runs
$127,600–$191,400
across 38 roles with salary data.
The Data Privacy Delivery Lead manages the execution and continuous improvement of enterprise data privacy capabilities. This hands-on product and delivery leadership role involves translating strategic direction, regulatory obligations, and business needs into prioritized backlogs, technical requirements, and high-quality solutions. The individual is responsible for defining what must be built, ensuring technical feasibility, and overseeing the full lifecycle from intake through implementation and operational support. Key responsibilities include establishing data profiling standards, managing roadmaps, and coordinating across legal, compliance, and engineering teams. The role requires proficiency in relational databases, cloud platforms, SQL, transformations, metadata, lineage, and reporting tools like Snowflake and Tableau. The position solves the challenge of converting complex regulatory requirements into actionable technical designs while ensuring that final outputs remain accessible and usable for non-technical stakeholders within a highly regulated environment.
Translate strategic goals and regulatory requirements into prioritized product backlogs, delivery plans, and clear acceptance criteria.
Define technically feasible requirements for developers and partners to ensure they can execute work without needing further clarification.
Apply technical knowledge of data platforms and architectures to evaluate implementation options and guide design decisions.
Establish data standards including business rules, classifications, naming conventions, and validation criteria for the delivery team.
Review designs, prototypes, and completed work to identify logic gaps, quality concerns, and usability barriers before release.
Direct the creation of data structures and reports that are understandable and actionable for non-technical stakeholders.
Manage the full project lifecycle from discovery and development through testing, training, and transition to support.
Evaluate opportunities to improve processes using AI, automation, and emerging technologies while ensuring audit readiness.
What we're looking for
Must have 5+ years of experience in data product delivery, engineering, management, governance, privacy, compliance, or a related discipline.
Must demonstrate experience converting business or regulatory objectives into backlogs, detailed requirements, milestones, and acceptance criteria.
Must possess technical fluency in enterprise data environments including relational databases, cloud platforms, SQL, transformations, metadata, and reporting solutions.
Must be able to evaluate the feasibility of data solutions and identify technical limitations or dependencies during planning.
Must have experience defining field-level and record-level requirements, including business definitions, transformation rules, and exception handling.
Must possess working knowledge of data profiling and validation methods to assess accuracy, consistency, and usability.
Must be able to review technical designs and prototypes to identify gaps, faulty assumptions, or quality concerns before release.
Must have experience shaping data outputs for non-technical audiences using plain language and consistent formatting.
Experience as a Product Owner, Data Engineer, or in similar roles is preferred.
Experience with Snowflake, Tableau, or other enterprise reporting tools is preferred.
Experience supporting privacy, compliance, governance, audit, risk management, or regulatory programs is preferred.
Knowledge of data inventory, metadata management, lineage, and quality frameworks is preferred.
Familiarity with AI-enabled products, automation, low-code platforms, and modern cloud ecosystems is preferred.
Experience working with Agile teams and vendor-managed solutions is preferred.
Insurance or other highly regulated industry experience is preferred.
Data Governance
Information Management
Data Engineering
Risk Management
Audit
Information Architecture
Compliance
Data Management Strategy
CIMP
IGP
CDMP
Python
Go
Java
Scala
C++
Rust
Microservices
APIs
Data Governance
Encryption
Anonymization
Pseudonymization
Machine Learning
Data Pipelines
Audit Logging
Threat Modeling
Data Lineage
Privacy-by-Design