Head of Data, International

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