Head of Data, International
Company Overview
Acrisure is a fintech leader that has evolved from a top 10 global insurance broker into a rapidly growing technology company. With expertise in insurance, reinsurance, real estate services, cyber services, and asset & wealth management, Acrisure uses AI and robotic process automation to transform the insurance value chain. The company delivers innovative solutions through established regional agencies, reaching millions of clients across the US and around the world. Acrisure's tech-forward approach drives value creation and improves outcomes across the financial services ecosystem.
Job Summary
The Head of Data, International will lead the design, implementation, and operation of Acrisure's next-generation data platforms that power the company's analytics capabilities. This role will partner with the data engineering leadership in North America in building a consolidated data foundation. This role will lead a data engineers with help of consultants and build scalable, resilient data solutions that support Acrisure's business functions and lines of business. The ideal candidate will combine deep technical expertise in cloud data lakes (Palantir, Databricks, Snowflake) and cloud platforms (Google Cloud, Azure) with strategic leadership skills to drive the technical vision and implementation of enterprise data solutions. This position plays a crucial role in Acrisure's data-driven transformation efforts.
Key Responsibilities
Strategic Leadership & Vision
Develop and execute the technical vision and roadmap for Acrisure's data engineering function, especially for all the data outside of North America.
Partner with Analytics partners and business stakeholders to understand requirements and translate them into effective data solutions
Stay current with emerging technologies and industry trends to continually evolve data engineering capabilities
Serve as a trusted advisor to executive leadership on data engineering matters
Platform Development & Architecture
Lead the design, implementation, and evolution of enterprise-scale data platforms using Azure, Palantir, Databricks and other modern data technologies
Lead development of enterprise semantic layer to serve as one stop data shop for all global consumers, utilizing Palantir Ontology, and/or other technologies
Establish architectural standards and best practices for data ingestion, processing, storage, and access
Ensure data platforms meet enterprise requirements for scalability, reliability, security, compliance and performance
Lead the implementation of data governance and data quality frameworks within data engineering systems
Team Leadership & Development
Build, mentor, and lead a high-performing team of data engineers and leaders
Set clear objectives and performance standards for the data engineering function
Implement agile development methodologies and DevOps practices to accelerate delivery
Foster a culture of innovation, continuous learning, and technical excellence
Collaborate with other technology and analytics leaders to ensure cohesive solutions
Operational Excellence
Establish metrics and monitoring to ensure reliable data platform operations
Implement disaster recovery and business continuity solutions for critical data assets
Create processes for incident management, change management, and capacity planning
Optimize cloud resource utilization to manage costs while meeting performance requirements
Client & Business Focus
Translate business needs into effective data engineering solutions
Ensure data engineering initiatives align with and support business objectives
Partner closely with Analytics teams to understand requirements and design solutions
Build strong relationships with business functions (Finance, HR, GTM, Customer Success, Product) and business lines (North America - Retail, North America - Specialty, International, Benefits & Pay, Reinsurance)
Develop dashboard and reporting mechanisms to demonstrate value and ROI of data engineering investments
Required Qualifications
Bachelor’s degree in computer science, Information Technology, or related field; Master's degree preferred
10+ years of experience in progressively responsible data engineering roles
At least 6 years of experience in leadership positions building and managing engineering teams of 20+ professionals
Proven expertise in cloud data lake technologies such as Palantir (highly preferred), Databricks, Snowflake
Strong experience with major cloud platforms (Google Cloud, Azure) and their respective data services
Deep understanding of data modeling, data warehousing, and data pipeline development
Experience implementing data governance, security, and compliance controls
Strong understanding of modern software development practices including CI/CD, testing, and version control
Experience managing data projects in financial services, insurance, or similar regulated industries preferred
Track record of successful delivery of large-scale, enterprise data initiatives
Excellent communication skills, both written and verbal, with the ability to translate complex technical concepts to business audiences
Preferred Skills & Competencies
Experience with real-time data processing and streaming technologies (Kafka, Spark Streaming, etc.)
Knowledge of machine learning operations (MLOps) and supporting data science workloads
Experience with data mesh and/or data fabric architectural approaches
Proficiency in multiple programming languages (Python, Scala, Java, etc.)
Understanding of API development and integration patterns
Strong project management and program management skills
Demonstrated client focus and ability to build strong stakeholder relationships
Expertise in agile methodologies and team leadership
Ability to influence and drive consensus across organizational boundaries
Track record of mentoring and developing engineering talent
