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Data Architect

Role overview

Qualifications

  • Bachelor’s degree in computer science or relevant field
  • 3-5 years of experience in data architecture, data engineering
  • Strong data modeling expertise
  • Advanced ELT/ETL development experience

Responsibilities

  • Design and maintain enterprise data architecture aligned to business domains
  • Build ELT/ETL pipelines using modern cloud-native tools
  • Partner with business stakeholders to translate requirements into scalable data structures
  • Mentor SQL developers and analytics engineers transitioning into modern data engineering roles

About the company

Coverys logo

Coverys

Insurance

With healthcare’s constant complexities and distractions, it can be difficult to focus on patients. Coverys can help with proven medical professional liability insurance, data analytics, risk mitigation resources, and more. You can count on Coverys for protection and services that help you stay focused on improving clinical, operational, and financial outcomes.

Company details

Company typeSME
IndustryInsurance
Company size501 - 1000

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Job description

Position Summary

The Data Architect will help design, build, and evolve our next‑generation enterprise data platform & data integration pipeline. This role is central to our transformation toward a modern, governed, cloud‑based data ecosystem that supports all functions at Coverys (notably underwriting, claims, actuarial, finance, and enterprise analytics etc.)

The Data Architect will help define the architectural blueprint, establish data modeling standards, and guide the development of scalable, automated data pipelines in Snowflake.  In addition to design of the architecture, this position will work closely with business and technology teams to ensure data is accurate, trusted, and available for advanced analytics, reporting, and operational decision‑making.

Essential Duties & Responsibilities

Data Architecture & Modeling

  • Design and maintain enterprise data architecture aligned to business domains (Policy, Party, Claims, Billing, Underwriting, etc.).

  • Ensure data architecture design aligns to enterprise architecture standards & partners closely with Enterprise Architecture.

  • Develop canonical and semantic data models to support analytics, reporting, and operational use cases.

  • Define standards for data modeling, data quality, naming conventions, metadata, lineage, and documentation.

  • Partner with business stakeholders to translate requirements into scalable data structures.

Data Engineering & Pipeline Development

  • Build ELT/ETL pipelines using modern cloud-native tools and frameworks.

  • Lead the migration from legacy batch processes to automated, event-driven, or CDC-based ingestion patterns.

  • Implement data quality rules, validation frameworks, and reconciliation logic.

  • Optimize Snowflake workloads for performance, cost, and reliability.

Cloud Data Platform Leadership

  • Design and oversee medallion-style data layers (bronze/silver/gold) for ingestion, curation, and consumption.

Governance, Standards & Best Practices

  • Work with Data Governance to establish data dictionaries, lineage, classification, data quality and stewardship models.

  • Ensure consistent use of canonical identifiers across systems and domains.

  • Promote data-as-a-product principles and guide teams toward reusable, scalable data assets.

Collaboration & Leadership

  • Partner with business analysts, data scientists, actuaries, and analytics teams to support data needs.

  • Mentor SQL developers and analytics engineers transitioning into modern data engineering roles.  Mentor and coach the data engineering team & lead the development of pipeline and architecture platforms.

  • Provide architectural oversight for major data initiatives across the enterprise.

  • Support evolving business needs, as applicable.

Education, Experience, Competencies & Values

  • Bachelor’s degree in computer science or relevant field from an accredited college or university, required.

  • 3-5- years of experience in data architecture, data engineering, required.

  • Strong data modeling expertise (conceptual, logical, physical).

  • Hands-on experience designing enterprise data architectures.

  • Advanced ELT/ETL development experience (preferably cloud-native).

  • Deep experience with cloud data warehouses, ideally Snowflake.

  • Proficiency in Python for data engineering and automation.

  • Strong SQL skills and experience with large-scale data processing.

  • Experience with data quality frameworks, metadata management, and lineage.

  • Understanding of modern data patterns (CDC, event-driven ingestion, APIs, streaming, orchestration).

  • Experience in the insurance industry, preferred.

  • Snowflake certification, a plus.

  • Familiarity with tools such as dbt, Airflow, Azure Data Factory, or similar.

  • Knowledge of MDM, canonical modeling, and governance frameworks.

  • Experience with Power BI or other BI tools.

  • Qualified candidates must be eligible to work in the US without sponsorship or restriction.

Base salary range is $96,650 - 130,755. Individual compensation packages are based on a variety of factors that are unique to each candidate including location, skill set, experience, qualifications and education.

If you're a caring and customer focused individual who enjoys working with passionate team members, Coverys is the right company for you!

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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