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. Withexpertisein insurance, reinsurance, real estate services, cyberservices, andasset & 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 willpartner with the data engineering leadership in North America in building aconsolidateddata foundation. This role willlead adata engineerswithhelpofconsultantsandbuild scalable, resilient data solutions that support Acrisure's business functions and lines of business. The ideal candidate will combine deep technicalexpertisein 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
1. Develop and execute the technical vision and roadmap for Acrisure's data engineering function, especially for all the data outside of North America.
2. Partner withAnalytics partners andbusiness stakeholders to understand requirements and translate them into effective data solutions
3. Stay current with emerging technologies and industry trends to continually evolve data engineering capabilities
4. Serve as a trusted advisor to executive leadership on data engineering matters
Platform Development & Architecture
5. Lead the design, implementation, and evolution of enterprise-scale data platforms usingAzure,Palantir,Databricksand other modern data technologies
6. Lead development of enterprisesemanticlayer to serve as one stopdata shop for all global consumers,utilizingPalantir Ontology, and/orothertechnologies
7. Establish architectural standards and best practices for data ingestion, processing, storage, and access
8. Ensure data platforms meet enterprise requirements for scalability, reliability, security,complianceand performance
9. Lead the implementation of data governance and data quality frameworks within data engineering systems
Team Leadership & Development
10. Build, mentor, and lead a high-performing team of data engineersand leaders
11. Set clearobjectivesand performance standards for the data engineering function
12. Implement agile development methodologies and DevOps practices to accelerate delivery
13. Foster a culture of innovation, continuous learning, and technical excellence
14. Collaborate with other technology and analytics leaders to ensure cohesive solutions
Operational Excellence
15. Establish metrics andmonitoringto ensure reliable data platform operations
16. Implement disaster recovery and business continuity solutions for critical data assets
17. Create processes for incident management, change management, and capacity planning
18. Optimizecloud resourceutilizationto manage costs while meeting performance requirements
Client & Business Focus
19. Translate business needs into effective data engineering solutions
20. Ensure data engineering initiatives align with and support business objectives
21. Partner closely with Analytics teams to understand requirements and design solutions
22. 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)
23. Develop dashboard and reporting mechanisms todemonstratevalue and ROI of data engineering investments
Required Qualifications
24. Bachelor’s degree in computer science, Information Technology, or related field;Master'sdegree preferred
25. 10+ years of experience in progressively responsible data engineering roles
26. At least6years of experience in leadership positions building and managing engineering teams of 20+ professionals
27. Provenexpertisein cloud data lake technologies such asPalantir(highly preferred),Databricks, Snowflake
28. Strong experience with major cloud platforms (Google Cloud, Azure) and their respective data services
29. Deep understanding of data modeling, data warehousing, and data pipeline development
30. Experience implementing data governance, security, and compliance controls
31. Strong understanding of modern software development practices including CI/CD, testing, and version control
32. Experience managing data projects in financial services, insurance, or similar regulated industries preferred
33. Track recordof successful delivery of large-scale, enterprise data initiatives
34. Excellent communication skills, both written and verbal, with the ability to translate complex technical concepts to business audiences
Preferred Skills & Competencies
35. Experience with real-time data processing and streaming technologies (Kafka, Spark Streaming, etc.)
36. Knowledge of machine learning operations (MLOps) and supporting data science workloads
37. Experience with data mesh and/or data fabric architectural approaches
38. Proficiencyin multiple programming languages (Python, Scala, Java, etc.)
39. Understanding of API development and integration patterns
40. Strong project management and program management skills
41. Demonstrated client focus and ability to build strong stakeholder relationships
42. Expertisein agile methodologies and team leadership
43. Ability to influence and drive consensus across organizational boundaries
44. Track recordof mentoring and developing engineering talent