Executive Director, Cloud Data Platforms & Engineering

Reinsurance Group of America, Incorporated•Remote, Florida, United States of America, FL

2d•$150,770 - $224,640

About The Position

The Executive Director, Cloud Data Platforms & Engineering is a senior technology leader responsible for defining and executing the enterprise strategy for modern, cloud-based data platforms. This role leads the design, delivery, and reliable operation of scalable, secure, and governed data platforms that power analytics, data science, and AI/ML initiatives across the organization. The leader will oversee a diverse portfolio of data platform capabilities — including cloud data warehouses and Lakehouses (e.g., Snowflake, Databricks), data integration and transformation (e.g., dbt, Informatica Data Management Cloud, Alteryx, Qlik), pipeline orchestration (e.g., Astronomer/Airflow), and data observability (e.g., Monte Carlo) — while driving platform standardization, automation, and measurable business value. This role balances platform modernization with operational stability and disciplined delivery, partnering across technology, business, and governance functions to ensure the data platform ecosystem accelerates enterprise outcomes.

Requirements

Bachelor’s Degree in Arts/Sciences (BA/BS) in computer science, Engineering, Information Systems, or related discipline - required
12+ Years of progressive experience in data engineering, data platform engineering, or enterprise data infrastructure, with 5+ years in senior or executive leadership roles -required
Proven experience leading enterprise-scale cloud data platform initiatives, including modern data warehouses, Lakehouses, and cloud-native data ecosystems (e.g., Snowflake, Databricks, or equivalent) - required
Experience implementing data governance, security, and regulatory compliance frameworks in cloud data environments, including access control, data classification, and lineage - required
Deep understanding of modern data engineering tooling across the full platform lifecycle — including data integration, transformation (e.g., dbt, Informatica), pipeline orchestration (e.g., Airflow/Astronomer), and data observability (e.g., Monte Carlo). - required
Strong knowledge of cloud architectures (AWS, Azure, or GCP) and experience designing secure, scalable, and cost-efficient data platform infrastructure. - required
Demonstrated ability to build, scale, and lead platform engineering teams supporting multiple business domains, global operations, or complex organizational structures. - required
Track record of driving platform standardization, Infrastructure as Code (IaC), CI/CD for data pipelines, and operational automation to reduce manual effort and improve reliability. - required
Strong business acumen with experience building investment cases, managing platform budgets, and aligning technology investments to measurable business outcomes (FinOps). - required
Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts for executive and non-technical audiences. - required

Nice To Haves

Master’s degree in Arts/Sciences (MA/MS) - preferred
Experience modernizing legacy data environments and leading large-scale platform migrations with minimal business disruption - preferred
Insurance, reinsurance, or regulated industry experience - preferred
Familiarity with data quality engineering, including automated testing, anomaly detection, and data contract frameworks at the dataset or metric level. - preferred

Responsibilities

Build, lead, and develop an established, high-performing, globally distributed platform engineering team, fostering a culture of technical excellence, accountability, and continuous improvement.
Define and execute the enterprise cloud data platform strategy, aligning platform investments with business priorities, data/AI objectives, and long-term technology roadmaps.
Lead the engineering and operations of the full data platform ecosystem — including cloud data warehouses/Lakehouses, data integration, transformation, orchestration, observability, and data quality services.
Establish and enforce technology standards, reference architectures, and engineering guardrails that ensure platform consistency, scalability, security, and interoperability across the data ecosystem.
Drive platform adoption and enablement across analytics, data science, and business teams by delivering self-service capabilities, reusable data products, and well-documented platform services.
Partner with business, product, and technology leaders to translate data needs into prioritized platform capabilities and investment cases with clear ROI.
Embed robust data governance, security, and regulatory compliance controls into platform design and operations, ensuring least-privileged access, data classification, lineage, and auditability.
Own platform reliability, performance, and cost optimization (FinOps) — establishing SLOs/SLAs, monitoring frameworks, incident response protocols, and unit-cost accountability for cloud data services.
Manage strategic vendor relationships, technology evaluations, and licensing negotiations to optimize the platform ecosystem and maintain a forward-looking technology roadmap.
Define and track measurable outcomes (KPIs/OKRs) for platform value realization, adoption, delivery predictability, and operational excellence — reporting progress to executive leadership.
Drives reliability, cost efficiency, and continuous improvement through metric-driven operations.
Attracts, develops, and retains top engineering talent with clear career paths and a strong team culture.