Verisk Analytics

Principal Data Architect

Verisk Analytics • $150K — $180K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Significant experience in data engineering or database architecture with recent ownership of data architecture in AWS environments.
  • Strong background in designing enterprise data platforms for operational and analytical workloads.
  • Deep understanding of varied data modeling techniques, including both relational and NoSQL approaches.
  • Proficient in SQL and database technologies like PostgreSQL, SQL Server, Aurora, and DynamoDB.
  • Practical experience with AWS architecture patterns such as data lakes, lakehouses, and event-driven systems.
  • Familiarity with data governance practices and operational handling of data products.
  • Experience with infrastructure as code and CI/CD methodologies.

Responsibilities

  • Define the target data architecture and phased roadmap for various data systems and products.
  • Establish and clarify domain-oriented data models to enhance data ownership and reduce duplication.
  • Design models and schemas across relational and NoSQL environments to meet diverse data needs.
  • Set standards for data operations, including ingestion, transformation, and retention processes.
  • Architect solutions using AWS data services such as S3, Glue, and Redshift among others.
  • Integrate transactional applications with advanced analytics and reporting while ensuring operational integrity.
  • Define standards for data metadata, lineage, and quality to ensure trust and understanding of data.

Benefits

  • Flexible work environment with hybrid options.
  • Opportunities for professional development and training.
  • Collaborative culture with cross-functional teams.
  • Access to the latest AWS services and technologies.
  • Focus on innovative data solutions in the insurance sector.
Full Job Description
Job Description

We are looking for a Data Architect to establish the architecture, standards, and roadmap that enable trusted data to move effectively across our AWS-based products and platforms. You will connect operational, analytical, and external data needs, defining how data is modeled, integrated, governed, secured, and consumed. The role requires a practical architect who can work across software engineering, data engineering, analytics, product, security, and business teams to turn complex insurance data into durable, reusable data products.

Responsibilities

  • Define the target data architecture and phased roadmap for operational systems, data lakes, warehouses, integration services, analytics platforms, and customer-facing data products.
  • Establish domain-oriented data models and product boundaries that clarify ownership, reduce duplication, and support consistent use of core business data.
  • Design logical and physical models, canonical schemas, event structures, data contracts, and master and reference data approaches across relational, dimensional, and NoSQL environments.
  • Set architecture standards for data ingestion, transformation, storage, sharing, retention, archiving, and deletion across batch, streaming, API, and event-driven patterns.
  • Architect AWS data solutions using appropriate services such as S3, Lake Formation, Glue, Redshift, Aurora, RDS, DynamoDB, Kinesis, Lambda, Step Functions, SQS, SNS, and API Gateway.
  • Connect transactional applications with reporting, business intelligence, advanced analytics, machine learning, and external customer use cases without compromising operational integrity.
  • Define expectations for metadata, cataloging, lineage, provenance, quality, observability, semantic consistency, and service levels so data can be understood and trusted.
  • Embed privacy and security into data design, including IAM, encryption, masking, tokenization, tenant isolation, policy-based access, auditability, retention, and permitted-use controls.
  • Guide database and workload design across relational, NoSQL, warehouse, and object storage technologies, including partitioning, indexing, query patterns, scalability, reliability, and cost.
  • Partner with product and business teams to translate information needs into data capabilities, making dependencies, constraints, and trade-offs explicit.
  • Evaluate new AWS services, data patterns, and platform capabilities through focused proofs of concept and evidence-based recommendations.
  • Provide architecture oversight from discovery through production and coach data engineers, software engineers, analysts, and technical leads in effective data design


Qualifications

  • Significant experience in data engineering, database architecture, analytics engineering, or software engineering, including recent ownership of data architecture in AWS environments.
  • A strong record of designing enterprise data platforms and data-intensive products that serve both operational and analytical workloads.
  • Deep expertise in data modeling, including relational, dimensional, domain-driven, event-based, document, key-value, and other NoSQL approaches.
  • Strong SQL and database engineering knowledge across technologies such as PostgreSQL, SQL Server, MySQL, Aurora, Redshift, and DynamoDB.
  • Practical understanding of data lake, lakehouse, warehouse, streaming, event-driven, and API-based architecture patterns on AWS.
  • Experience designing data pipelines and integrations using services such as AWS Glue, Kinesis, Lambda, Step Functions, SQS, SNS, and APIs.
  • Strong knowledge of data governance, metadata, lineage, quality, privacy, security, retention, access control, and the operational ownership of data products.
  • Experience using infrastructure as code and CI/CD practices to make data platforms repeatable, controlled, testable, and supportable.
  • Ability to communicate complex data concepts, architecture choices, dependencies, and risks to technical teams, product leaders, and business stakeholders.
  • Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Mathematics, or a related discipline, or equivalent professional experience.

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About Verisk Analytics

Verisk Analytics is a data analytics company that provides data, analytics, and decision-support services to professionals in insurance, energy, healthcare, financial services, government, and risk management. The company uses proprietary data sets and algorithms to provide predictive analytics and decision support solutions to its clients. Verisk Analytics was founded in 1971 and is headquartered in Jersey City, New Jersey.
Learn more about Verisk Analytics
Size
9,367 employees
Market Cap
$27.2 billion
Industry
Net Income
$712.7 million
Founded
1971
5 Year Trend
+8.5%
Revenue
$2.7 billion
NASDAQ

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