Data Architect

We are seeking an experienced Cloud Native AWS Data Architect to lead the design and implementation of modern data platforms and analytics solutions for the insurance industry. The ideal candidate will bring strong expertise in AWS data services, big data processing, data modeling, enterprise analytics, and cloud-native architectures.

This role requires a hands-on technical leader who can drive data architecture decisions, mentor engineering teams, and ensure delivery of secure, scalable, cost-optimized, and high-performance data solutions supporting reporting, dashboards, advanced analytics, and data products.

For over 50 years, Verisk has been the leading data analytics and technology partner to the global insurance industry by delivering value to our clients through expertise and scale. We empower communities and businesses to make better decisions on risk, faster.

At Verisk, youll have the chance to use your voice and build a rewarding career thats as unique as you are, with work flexibility and the support, coaching, and training you need to succeed.

For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work for outstanding workplace culture in the US, fourth consecutive year in the UK, Spain, and India, and second consecutive year in Poland. We value learning, caring, and results and make inclusivity and diversity a top priority.

In addition to our Great Place to Work Certification, weve been recognized by The Wall Street Journal as one of the Best-Managed Companies and by Forbes as a Worlds Best Employer and Best Employer for Women, testaments to the value we place on workplace culture.

Were 7,000 people strong. We relentlessly and ethically pursue innovation. And we are looking for people like you to help us translate big data into big ideas. Join us and create an exceptional experience for yourself and a better tomorrow for future generations.

Verisk Businesses

• Underwriting Solutions- provides underwriting and rating solutions for auto and property, general liability, and excess and surplus to assess and price risk with speed and precision
• Claims Solutions- supports end-to-end claims handling with analytic and automation tools that streamline workflow, improve claims management, and support better customer experiences
• Property Estimating Solutions- offers property estimation software and tools for professionals in estimating all phases of building and repair to make day-to-day workflows the most efficient
• Specialty Business Solutions- provides an integrated suite of software for full end-to-end management of insurance and reinsurance business, helping companies manage their businesses through efficiency, flexibility, and data governance
• Catastrophe and Risk Solutions- provides risk modeling solutions to help individuals, businesses, and society become more resilient to catastrophic events
• Marketing Solutions- delivers data and insights to improve the reach, timing, relevance, and compliance of every consumer engagement
• Life Insurance Solutions- offers end-to-end, data insight-driven core capabilities for carriers, distribution, and direct customers across the entire policy lifecycle of life and annuities for both individual and group
• Verisk Maplecroft- provides intelligence on sustainability, resilience, and ESG, helping people, business, and societies become stronger

About Us

Verisk Analytics is an equal opportunity employer. Verisk invests in a benefits package for all employees that includes the following:

• Health Insurance
• a Retirement Plan
• Disability benefits
• a Paid Time Off program
• We offer a competitive total rewards package that includes base salary determined based on role, experience, skill set, and location

All members of the Verisk Analytics family of companies are equal opportunity employers. We consider all qualified applicants for employment without regard to race, religion, color, national origin, citizenship, sex, gender identity and/or expression, sexual orientation, veterans status, age or disability. Verisk's minimum hiring age is 18 except in countries with a higher age limit subject to applicable law.

Job Requirements

• Bachelor's degree in Computer Science, Software Engineering, Mathematics, or related field; Master's preferred
• 8+ years of progressive experience in data engineering/analytics engineering/platform engineering, with 3+ years in a Data Architect/AWS Data Architecture leadership role
• Proven experience designing and implementing AWS-native analytics platforms, data lakes/lakehouse, and enterprise-scale BI/analytics architectures
• Strong hands-on expertise with AWS data services including S3, Glue, Athena, Redshift, EMR, Lake Formation, RDS/Aurora, and orchestration tools like Step Functions/Airflow/MWAA
• Experience with big data processing using Spark/PySpark, and modern data engineering approaches (partitioning, compaction, incremental processing, CDC patterns)
• Deep proficiency in SQL, performance tuning, and scalable design for analytical workloads
• Strong understanding of data modeling, metadata/catalog strategies, and data governance concepts
• Strong understanding of multi-tenant architectures and secure data isolation strategies for analytics workloads
• Familiarity with Agile/Scrum methodologies and experience collaborating across product, engineering, and data teams
• Knowledge of infrastructure-as-code tools such as Terraform, CloudFormation, or CDK
• Strong communication skills, ability to influence stakeholders, and ability to drive architecture across multiple teams

Preferred Skills

• Expertise building scalable S3-based Data Lakes/Lakehouse architectures and open table formats (Apache Iceberg/Delta Lake/Hudi)
• Strong experience with Amazon Redshift (RA3/Serverless) including performance tuning, workload management, Spectrum, and cost optimization
• Proven ability to design and implement data pipelines using AWS Glue, EMR/Spark, Athena, Step Functions including batch and event-driven ingestion patterns
• Experience integrating RDS/Aurora (PostgreSQL/MySQL) into analytics ecosystems, including replication/CDC and OLTP-to-analytics data flows
• Familiarity with BI platforms such as Power BI, Tableau, QuickSight, Looker, and semantic modeling approaches
• Understanding of data governance practices including data classification, stewardship, lineage, and access controls

Job Responsibilities

• Lead the architecture, design, and implementation of cloud-native data platforms - including ingestion, storage, processing, metadata management, governance, and analytics enablement
• Define and own data architecture standards, including patterns for data lakes, lakehouse, data warehousing, data marts, and scalable analytics solutions on AWS
• Collaborate with product management, business stakeholders, and cross-functional teams to translate business requirements into data products and analytics solutions
• Drive domain-driven data modeling, including canonical data models, dimensional models, and entity relationships aligned to business domains
• Design and implement scalable data pipelines (batch and streaming) using AWS and modern big-data frameworks (e.g., Spark, EMR, Glue, Athena, Step Functions)
• Architect data solutions leveraging S3-based Data Lake/Lakehouse patterns using open formats like Parquet/Iceberg/Delta (where applicable)
• Build and govern enterprise analytics ecosystems, including semantic layer design, KPI definitions, and reusable curated datasets for BI and downstream consumers
• Design and optimize data warehouses and analytical query platforms using Amazon Redshift (RA3/Serverless), Athena, and federated query patterns
• Ensure robust data quality, lineage, observability, and monitoring, integrating with tools/services such as CloudWatch, Dynatrace, data pipeline metrics, and automated validation checks
• Implement security best practices in data architecture including IAM, encryption (KMS), row/column-level security, PII handling, data masking, and regulatory compliance controls
• Familiar with version-controlled pipelines, CI/CD automation, environment promotion, and infrastructure-as-code (Terraform/CloudFormation/CDK)
• Architect event-driven and near-real-time analytics solutions using services such as Kafka/MSK, Kinesis, SQS/SNS, and streaming ingestion frameworks
• Conduct proof-of-concept initiatives to evaluate emerging AWS services and tools that improve performance, cost, and developer productivity
• Mentor engineering and analytics teams on architecture best practices, query performance optimization, modeling standards, and scalability patterns