Lead Data Architect

Coverys; New York (NY); On-site; USD 122,000 - 165,000; Full time

Job summary

Coverys is seeking a Lead Data Architect to drive the design, build, and evolution of a modern cloud-based data platform with Snowflake. You will set architectural standards, model data for analytics, and lead scalable ELT/ETL pipelines while partnering with business and tech teams to ensure trusted data for reporting and decision making.

The role combines hands-on engineering leadership with strategic governance, data quality, and guardrails, mentoring the data engineering team and aligning

Qualifications

• Bachelor’s degree in computer science or related field.
• 5–10 years in data architecture/engineering with leadership.
• Strong data modeling (conceptual, logical, physical).
• Hands-on design of enterprise data architecture.
• Cloud-native ELT/ETL experience.
• Deep Snowflake experience.
• Python for data engineering/automation.
• Strong SQL for large-scale processing.
• Experience with data quality, metadata, lineage.
• Insurance industry experience preferred.
• Snowflake certification a plus.
• Familiar with governance and MDM.
• Experience with Power BI or BI tools.

Responsibilities

• Lead the design and maintenance of the enterprise data architecture aligned to business domains (Policy, Party, Claims, Billing, Underwriting, etc.).
• Ensure data architecture design aligns to enterprise architecture standards and partners 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 and provide technical recommendations and tradeoffs.
• Lead the 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.
• Design and build reusable data engineering frameworks, shared components, and reference implementations.
• Evaluate emerging data technologies and lead proofs of concept for enterprise adoption.
• Define engineering guardrails for security, observability, resiliency, recoverability, and readiness of data products.
• Mentor the Engineering team to ensure adherence to standards and best practices.

Skills

Data modeling

Python

SQL

Power BI

Snowflake

ETL/ELT

Cloud data warehousing

Data governance

Mentoring

Leadership

Education

Bachelor’s degree

Tools

dbt

Airflow

Azure Data Factory

Job description

Position Summary

The Lead Data Architect will lead the design, build, and evolution of 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.)

Position Summary

The Lead Data Architect will lead the design, build, and evolution of 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 Lead Data Architect will define the architectural blueprint, establish data modeling standards, and lead the development of scalable, automated data pipelines in Snowflake. In addition to designing 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 Design & Modeling

• Lead the design and maintenance of the 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 and provide technical recommendations and tradeoffs.

Data Engineering & Pipeline Development

• Lead the 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 the most 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 that improve development speed, consistency, and reliability.
• Evaluate emerging data technologies and lead proofs of concept to determine practical adoption, integration, and enterprise scalability.
• Define and apply engineering guardrails for security, observability, resiliency, recoverability, and operational readiness of critical data products.
• Drive Snowflake workload optimization for performance, cost, and reliability.
• Mentor the Lead of the Engineering team to ensure solution adheres to the right standards.
• Ensure that the data engineering team is following sound technical processes and best practices.

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 and guide their implementation across data engineering solutions.
• 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 technical direction, review designs and code, and help remove delivery blockers.
• Provide architectural oversight and technical leadership 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.
• 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.
• Communicate designs clearly to the senior leadership team.
• Qualified candidates must be eligible to work in the US without sponsorship or restriction.

The base salary range for this role is $121,865 - $164,875. 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!