Data Architect

Coverys

1d•$96,650 - $130,755

About The Position

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.

Requirements

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

Nice To Haves

Experience in the insurance industry, preferred.
Snowflake certification, a plus.
Familiarity with tools such as dbt, Airflow, Azure Data Factory, or similar.
Experience with Power BI or other BI tools.

Responsibilities

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