Senior Director, Data Engineering

Starr Insurance•Atlanta, GA

About The Position

Starr Insurance Companies is a leading insurance and investment organization, providing commercial property and casualty insurance, including travel and accident coverage, to almost every imaginable business and industry in virtually every part of the world. Cornelius Vander Starr established his first insurance company in Shanghai, China in 1919. Today, we are one of the world’s fastest growing insurance organizations, capable of writing in 128 countries on 6 continents. Overview The Senior Director, Data Engineering is a senior leadership role, responsible for driving the transformation and execution of Starr’s enterprise data ecosystem in direct support of core insurance business functions—including underwriting, claims, risk, finance, and regulatory reporting. Reporting to the AVP, Financial Systems, this leader will oversee the design, build, and operation of robust enterprise data solutions that solve for complex integration challenges, accelerate business processes, and deliver trusted, timely insights. Central to this role is the consolidation and rationalization of fragmented, legacy regional data assets onto unified, scalable global operational data platforms. This leader will champion data engineering and warehousing best practices, focusing on efficient and automated data flows, high-performance processing, and proactive data quality management. The Senior Director will optimize and enable critical finance and actuarial workflows—such as month-end close cycles and daily general ledger/reinsurance data processing—while safeguarding reliability and compliance for business operations. You will be responsible for shaping the technical strategy and operational effectiveness of Starr’s Data Engineering function, building organizational capability, innovating processes and technologies, and forging deep partnerships with stakeholders across the insurance business.

Requirements

Significant hands-on expertise building, integrating, and supporting enterprise-scale data warehousing and engineering solutions in complex insurance environments.
Advanced proficiency with SQL, Informatica, SSIS as well as cloud-native data engineering platforms (Databricks, Azure Fabric), ETL/ELT orchestration, and automation frameworks.
Deep experience in migration and integration of legacy/regional systems and data assets into consolidated, standardized global platforms.
Strong working knowledge of Insurance business systems (Policy, Claims, Finance, Reinsurance), core data structures, and compliance/reporting requirements.
Proven ability to architect and operationalize solutions for daily financial data processing and reporting, reconciliation automation, and actuarial/finance workflow enablement.
Demonstrated skill in deploying and managing data quality, validation, reconciliation, and issue resolution frameworks.
Experience leading Insurance data engineering teams and building organizational capability in both legacy and modern data management approaches.
Bachelor’s or Master’s in Computer Science, Data Engineering, Information Systems, or related field; advanced degree preferred.
12+ years’ experience in enterprise data engineering, data integration, and platform delivery, with at least 5 years in senior leadership roles.
Extensive Insurance industry experience—particularly in financial, regulatory, and operational data management.
Proven track record leading and delivering complex data migrations, platform consolidations, and business-critical automation initiatives.
Expertise in mentoring and building high-performing teams skilled in modern data engineering and insurance data modeling.
Strong technical leadership, stakeholder management, program delivery, and communication skills.

Nice To Haves

Professional certifications in cloud platforms, data engineering, or insurance data management are highly desirable.

Responsibilities

Data Integration & Enterprise Warehousing Architect, design, and deliver scalable data integration solutions that consolidate, standardize, and enrich data from regional and legacy systems to global platforms for underwriting, claims, risk, finance, and regulatory domains.
Lead the migration of fragmented, heterogeneous datasets and overlapping regional warehouses into unified enterprise repositories, enforcing standard schemas and data models.
Ensure robust engineering of data warehouses/marts optimized for business processes, analytics, and regulatory reporting.
Business Process Automation & Data Flow Optimization Drive strategic initiatives to accelerate and optimize the month-end close cycle, with automation of reconciliations and enhanced data flows for finance and actuarial teams.
Oversee the transition from monthly batch processing of premium, claims, general ledger and reinsurance data to daily ingestion and transformation, enabling timelier, more accurate financial and risk reporting.
Data Quality & Reliability Establish systematic processes and tooling for proactive detection, monitoring, and resolution of data quality issues, ensuring the completeness, accuracy, and reliability of key data assets for operational and regulatory use.
Implement rigorous data validation, reconciliation, and lineage frameworks for transparent, auditable data delivery to stakeholders.
Legacy Rationalization & Platform Consolidation Analyze the enterprise data landscape to identify redundant, fragmented, or obsolete assets; lead their retirement and accelerate consolidation onto strategic, scalable global platforms.
Stakeholder Engagement & Delivery Collaborate intensively with business and technical stakeholders—underwriting, claims, risk, finance, compliance, and IT—translating functional needs into actionable data engineering solutions.
Advocate for and ensure business-aligned delivery, change management, and adoption of new processes and platforms across teams.
Team Leadership & Talent Development Build and lead a high-performing globally distributed data engineering team, fostering expertise in modern technologies, insurance data modeling, and operational best practices.
Mentor and develop talent in both technical proficiency and business domain knowledge, with emphasis on supporting well-modeled data warehouses/marts tailored for insurance operations.
Architecture Alignment & Technical Excellence Partner with Data Architecture leadership to align engineering design and delivery to enterprise reference architectures, governance frameworks, and quality standards.
Ensure data security (PII / data classification) practices are tightly implemented.
Continuous Improvement & Risk Management Institutionalize continuous improvement in engineering methodologies, automation, and platform resilience.
Own risk assessment, controls, and performance tracking for data engineering initiatives using defined KPIs and health metrics.