Data Engineer /AI

VeeRteq Solutions Inc.; Irving (TX); Remote; USD 140,000 - 210,000; Full time

Job summary

VeeRteq Solutions Inc. is seeking a senior Data Engineer / AI to design scalable Snowflake data models and pipelines, delivering bronze, silver, and gold data layers with reusable semantic assets for trusted analytics and natural-language data access.

You will collaborate across product, analytics, and engineering to translate complex requirements into governed data products and semantic models while optimizing performance, reliability, and cost.

Qualifications

• Healthcare/payer domain experience with member, claims data
• Expert Snowflake SQL with complex transforms and analytics
• Experience building bronze/silver/gold data layers
• Define business metrics and semantic views
• Snowflake Cortex analytics experience preferred
• Data quality, profiling and validation expertise
• Strong communication and cross-functional ownership

Responsibilities

• Design scalable Snowflake data models and pipelines
• Build bronze, silver and gold data layers and semantic assets
• Collaborate with product, analytics and engineering partners
• Optimize queries and configurations for cost and performance
• Implement data quality validation and testing
• Document data lineage and architectural decisions
• Use dbt to develop modular transformations and tests
• Support Cortex-enabled analytics and agent workflows
• Troubleshoot production issues and deliver durable solutions
• Maintain governance and semantic definitions

Skills

Healthcare domain

Communication

Ownership

Cross-functional

Problem solving

Tools

Snowflake SQL

Snowflake Data Eng

Semantic Modeling

Snowflake Cortex

dbt

Python

Job description

Job Title - Data Engineer /AI

Location - Remote USA

Experience - Min 10+ years

Skill Requirement

• Healthcare or payer domain experience, especially with member, claims, provider, quality, or reference data.
• Snowflake SQL: Highly skilled. Must be able to develop complex transformations, optimize performance, and work confidently with CTEs, advanced joins, and analytic/window functions.
• Snowflake Data Engineering: Strong real-world experience building curated data layers using medallion architecture principles across bronze, silver, and gold datasets.
• Semantic Modeling / Semantic Layer Engineering: Must be able to define business-friendly metrics, dimensions, grain, relationships, and reusable semantic views on top of Snowflake data.
• Snowflake Cortex / AI-Enabled Analytics: Experience supporting Snowflake Cortex-based analytics workflows, semantic intelligence, or agentic analytics use cases is strongly preferred.
• Data Quality, Profiling, and Validation: Must be able to identify natural and surrogate keys, assess cardinality and distribution, validate transformations, and ensure trustworthy semantic outputs.
• Strong communication and ownership: Able to work across engineering, product, and analytics partners, clarify requirements, and proactively drive work with limited direction.

Desirements

• Experience in evaluating / troubleshooting and measuring agent performance, identifying issues, and optimizing it
• Experience with dbt, semantic view design, or governed self-service analytics patterns.
• Python experience for automation, metadata processing, data validation, or AI-assisted engineering workflows.
• Exposure to agentic AI, natural language analytics, or Snowflake Cortex Analyst / Cortex Search use cases.
• Specific technologies to be used and level of proficiency :
• Snowflake SQL: Highly skilled to expert level.
• Snowflake: Strong hands-on experience with performance tuning, secure data design, and curated data modeling.
• Semantic Modeling / Semantic Views: Strong proficiency in defining business metrics, dimensions, relationships, grain, and reusable semantic abstractions.
• dbt: Preferred real-world experience developing modular transformations, tests, and deployment patterns.
• Snowflake Cortex: Preferred experience with Cortex-enabled analytics, semantic intelligence, or agent-supporting workflows.
• Python: Some experience desired, with preference for intermediate or higher skill for automation and validation use cases.

Day to day Job Description of a Senior Data AI Engineer role

• Design and implement scalable Snowflake data models and pipelines that align with business objectives and agentic AI use cases.
• Build curated bronze, silver, and gold data layers and reusable semantic assets that support trusted analytics and natural-language data access.
• Collaborate with product, analytics, and engineering partners to translate complex requirements into governed data products and semantic models.
• Optimize Snowflake queries, warehouse configurations, and transformation performance for reliability, scalability, and cost efficiency.
• Design and implement data quality validation, profiling, and testing strategies to improve trust in downstream semantic outputs.
• Contribute to lineage-aware transformation patterns, documentation, and engineering standards for reusable data assets.
• Use dbt where applicable to develop modular transformations, tests, and deployment patterns; prior hands-on dbt experience is preferred.
• Support Snowflake Cortex-enabled analytics, semantic intelligence, and agent-assisting workflows where applicable.
• Troubleshoot production issues and implement durable long-term solutions.
• Document architectural decisions, semantic definitions, and data lineage.