Data Architect (Insurance)

Remote
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AI Summary

Design, optimize, and maintain data architectures for insurance products and analytics. Collaborate with cross-functional teams to ensure data reliability and scalability. Implement data governance and security practices.

Key Highlights
Design scalable data models and pipelines
Collaborate with engineering and product teams
Implement data governance and security practices
Key Responsibilities
Design, document, and maintain scalable data models, data pipelines, and storage solutions
Architect and optimize cloud-based data platforms
Collaborate with engineering, product, actuarial, underwriting, and data science teams
Implement data governance, data quality, and metadata management practices
Technical Skills Required
Cloud data platforms (AWS, Azure, GCP) Data modeling (conceptual, logical, physical) Database design (relational and NoSQL systems) ETL/ELT pipelines Data orchestration tools (Airflow, dbt) Data warehousing SQL Distributed computing frameworks (Spark)
Benefits & Perks
Remote work
Contractual requirement
Nice to Have
Experience in the insurance or insurtech industry
Familiarity with insurance-specific data standards (ACORD)
Experience with data cataloging tools (Collibra, Alation)
Exposure to event-driven architecture (Kafka, Kinesis)

Job Description


Job Title: Data Architect

Location: Remote (Canada)

Contractual Requirement

About the Role:

Client is seeking a mid-level Data Architect with 3–7 years of experience to join our growing insurtech team. In this role, you will design, optimize, and maintain data architectures that power key insurance products, analytics, and operations. You’ll collaborate with cross-functional teams to ensure data is reliable, scalable, secure, and aligned with business needs in a fast-evolving insurance technology environment.


Key Responsibilities:

  • Design, document, and maintain scalable data models, data pipelines, and storage solutions for insurance products and analytics.
  • Architect and optimize cloud-based data platforms (e.g., AWS, Azure, and GCP) for performance, cost efficiency, and security.
  • Collaborate with engineering, product, actuarial, underwriting, and data science teams to understand data requirements.
  • Implement data governance, data quality, and metadata management practices.
  • Define and enforce data architecture standards, patterns, and best practices.
  • Support integration of third-party data sources, including telematics, claims data, customer data, and policy data.
  • Perform root cause analysis and troubleshoot complex data issues.
  • Partner with security teams to ensure compliance with industry regulations (e.g., HIPAA, SOC 2, state insurance requirements).
  • Evaluate new technologies, tools, and frameworks that can improve data capabilities.
  • Produce clear technical documentation, diagrams, and guidelines.


Required Qualifications:

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.
  • 3–7 years of experience in data architecture, data engineering, or a similar role.
  • Strong experience with cloud data platforms (AWS, Azure, or GCP).
  • Proficiency in data modeling (conceptual, logical, physical) and database design for relational and NoSQL systems.
  • Hands-on experience with ETL/ELT pipelines, data orchestration tools (e.g. Airflow, dbt), and data warehousing.
  • Strong SQL skills and familiarity with distributed computing frameworks (e.g., Spark).
  • Experience designing data solutions for analytics, reporting, and machine learning workflows.
  • Understanding of data security, privacy, and governance best practices.
  • Excellent communication and documentation skills.


Preferred Qualifications:

  • Experience in the insurance or insurtech industry (claims, underwriting, actuarial, policy lifecycle, regulatory reporting).
  • Familiarity with insurance-specific data standards (e.g., ACORD).
  • Experience with data cataloging tools (e.g., Collibra, Alation).
  • Exposure to event-driven architecture (Kafka, Kinesis, or similar).
  • Knowledge of API-based data integrations.


Soft Skills:

  • Strong problem-solving and analytical abilities.
  • Ability to work independently in a fully remote environment.
  • Collaborative mindset with the ability to translate business needs into technical solutions.
  • Detail-oriented approach with a focus on data quality and reliability.

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