Lead Data Architect

This is a fully remote position, open to applicants in Connecticut, +11 more states.

📋 Description

• Oversee the design, development, and advancement of Coverys’ next-generation enterprise data platform and integration pipeline.

• Establish the architectural framework and set data modeling standards.

• Guide enterprise data architecture in alignment with business domains such as Policy, Party, Claims, Billing, and Underwriting.

• Create canonical and semantic data models for analytics, reporting, and operational use cases.

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

• Convert business requirements into scalable data structures while providing technical recommendations and trade-offs.

• Direct the design and development of ELT/ETL pipelines utilizing modern cloud-native tools and frameworks.

• Lead the transition 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 enhanced performance, cost-efficiency, and reliability.

• Act as a hands-on technical expert for complex data engineering challenges, including pipeline design, performance tuning, scalability, and troubleshooting in production.

• Design and create reusable data engineering frameworks, shared components, and reference implementations.

• Assess emerging data technologies and spearhead proofs of concept.

• Define and enforce engineering guardrails for security, observability, resiliency, recoverability, and operational readiness.

• Mentor members of the engineering and data engineering teams, including SQL developers and analytics engineers transitioning to modern data engineering roles.

• Ensure adherence to sound technical processes and best practices within the data engineering team.

• Design and manage medallion-style data layers (bronze/silver/gold).

• Collaborate with Data Governance to create data dictionaries, lineage, classification, data quality, and stewardship models.

• Ensure consistent application of canonical identifiers across various systems and domains.

• Advocate for data-as-a-product principles and the development of reusable, scalable data assets.

• Collaborate with business analysts, data scientists, actuaries, and analytics teams.

• Provide technical direction, review designs and code, and eliminate delivery obstacles.

• Offer architectural oversight and technical leadership for significant enterprise data initiatives.

• Adapt to evolving business requirements as necessary.

⛳️ Requirements

• Bachelor’s degree in computer science or a related field from an accredited institution, required.

• 5-10 years of experience in data architecture and data engineering, including technical leadership experience, required.

• Expertise in data modeling (conceptual, logical, physical).

• Practical experience in designing enterprise data architecture.

• Advanced experience in ELT/ETL development, preferably in a cloud-native environment.

• Extensive experience with cloud data warehouses, ideally Snowflake.

• Proficient in Python for data engineering and automation.

• Strong SQL skills with a background in large-scale data processing.

• Familiarity 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 is preferred.

• Snowflake certification is 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.

• Proven experience in mentoring data engineering teams.

• Ability to clearly communicate designs to the senior leadership team.

• Candidates must be eligible to work in the US without sponsorship or restrictions.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off and holiday schedule.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements to promote work-life balance.