Lead Data Architect

Coverys

. Lead the design, build, and evolution of Coverys’ next-generation enterprise data platform and data integration pipeline .

Posted 9/22/2026full-timeRemote • United StatesSenior💰 $121,865 - $164,875 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data architecture and engineering, with a strong focus on designing and implementing scalable data platforms and integration pipelines. Proficient in data modeling, ELT/ETL processes, and cloud technologies, particularly Snowflake.

Highest-signal resume keywords

Data ArchitectureELT/ETL DevelopmentSnowflake OptimizationData Modeling ExpertiseTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingELT DevelopmentETL DevelopmentPythonSQLData Quality FrameworksMetadata ManagementLarge-Scale Data ProcessingCloud Data WarehousingModern Data Patterns

Soft Skills

MentoringCommunication

Tools & Technologies

SnowflakeDbtAirflowAzure Data FactoryPower BI

Certifications & Qualifications

Snowflake Certification

Industry Keywords

Insurance IndustryData GovernanceCanonical ModelingMDMData Quality

Tech Stack

Tools & technologies

AirflowAzureCloudETLPythonSQL

About the role

Key responsibilities & impact

Lead the design, build, and evolution of Coverys’ next-generation enterprise data platform and data integration pipeline
Define the architectural blueprint and establish data modeling standards
Lead enterprise data architecture aligned to business domains including Policy, Party, Claims, Billing, and Underwriting
Develop canonical and semantic data models for analytics, reporting, and operational use cases
Define standards for data modeling, data quality, naming conventions, metadata, lineage, and documentation
Translate business requirements into scalable data structures and provide technical recommendations and tradeoffs
Lead design and development of ELT/ETL pipelines using modern cloud-native tools and frameworks
Lead 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
Serve as a hands-on technical expert for complex data engineering challenges, including pipeline design, performance tuning, scalability, and production troubleshooting
Design and build reusable data engineering frameworks, shared components, and reference implementations
Evaluate emerging data technologies and lead proofs of concept
Define and apply engineering guardrails for security, observability, resiliency, recoverability, and operational readiness
Mentor engineering and data engineering team members, including SQL developers and analytics engineers transitioning into modern data engineering roles
Ensure the data engineering team follows sound technical processes and best practices
Design and oversee medallion-style data layers (bronze/silver/gold)
Partner 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 reusable, scalable data assets
Partner with business analysts, data scientists, actuaries, and analytics teams
Provide technical direction, review designs and code, and remove delivery blockers
Provide architectural oversight and technical leadership for major enterprise data initiatives
Support evolving business needs as applicable

Requirements

What you’ll need

Bachelor’s degree in computer science or relevant field from an accredited college or university, required
5-10 years of experience in data architecture and data engineering, including technical leadership experience, required
Strong data modeling expertise (conceptual, logical, physical)
Hands-on experience designing enterprise data architecture
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
Mentoring data engineering teams
Ability to communicate designs clearly to the senior leadership team
Qualified candidates must be eligible to work in the US without sponsorship or restriction