As a Senior Data Platforms Architect, you will play a key role in shaping our data platform strategy and ensuring the design, performance, and governance of our enterprise-wide cloud native data infrastructure. You will collaborate with stakeholders across risk, actuarial, underwriting, and finance to build a scalable and resilient data ecosystem.
Data Platform Architecture & Strategy
* Design and implement a scalable cloud-based data platform leveraging Snowflake, Azure, and Datavirtuality.
* Define best practices for data governance, security, compliance, and performance optimization in a regulated industry.
* Architect and optimize data storage, modeling, and processing solutions for structured and semi-structured data.
* Lead the integration of multiple data sources to create a unified, accessible, and efficient data environment.
* Translate reinsurance business processes into efficient data models to support risk assessment, underwriting, claims, and financial reporting.
Data Engineering & Development
* Build and maintain robust data pipelines using StreamSets, Alteryx, and Python.
* Ensure data availability, reliability, and scalability across all business functions.
* Implement real-time and batch data processing to support analytical and operational use cases.
* Optimize ETL/ELT workflows for high-performance data ingestion and transformation.
* Work with DevOps teams to implement CI/CD, infrastructure as code, and automation into data workflows.
Collaboration & Leadership
* Work closely with data engineers, analysts, and business teams to deliver high-impact data solutions.
* Act as a technical advisor to ensure alignment between data platform architecture and business needs.
* Mentor junior team members and provide technical leadership in data platform best practices.
* Communicate complex data concepts to non-technical stakeholders in a clear, actionable manner.
Qualifications
* 10+ years of experience in data platform architecture and engineering.
* Expertise in Snowflake, Datavirtuality and StreamSets.
* Proficiency in Python and SQL for data processing, automation, and optimization.
* Experience with data modeling, storage, and performance tuning in cloud environments.
* Strong knowledge of data governance, compliance, and security (experience in regulated industries like insurance, reinsurance, or financial services is a plus).
* Experience with batch & real-time data processing.
* Preferred: Experience in the reinsurance industry, with knowledge of reinsurance business processes and the ability to incorporate these into data models.
* Experience with AI/ML-driven data solutions in the (re)insurance domain is a plus.
* Familiarity with containerization (Docker, Kubernetes) for data workloads.
* Certifications in Snowflake are an advantage.
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