Job description
Lead Data Architect
Location: Remote, US based
Position type: Full Time Employee
Compensation: $190.000 (base + bonus)
Job Summary
Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and beyond. Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management. We have a diverse, global team of consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture. As part of our growth and upcoming initiatives, we are proactively searching for Lead Data Architects to support future data platform modernization initiatives across our client portfolio.
Position Summary
The Lead Data Architect will lead the architecture assessment, transition planning, and modernization of the client’s data platform. This role will be responsible for designing the future-state architecture, defining best practices for ELT pipelines, and guiding the migration of existing SQL-based transformations into a scalable dbt framework within a Snowflake environment.
The position will work closely with the client’s engineering teams and internal Data Meaning consultants, leading knowledge transfer sessions, architecture walkthroughs, and platform transition initiatives to ensure long-term scalability, reliability, and governance of the data platform.
Key Responsibilities:
Lead architecture assessment and documentation of the current data platform (Snowflake, Airflow, AWS)
Design the future-state data platform architecture following modern ELT and dbt best practices
Define standards for: data modeling, pipeline architecture, transformation frameworks, governance and data quality
Lead the migration of transformation logic into dbt models
Define architectural patterns for: staging layers, intermediate layers, data marts
Implement automated testing frameworks within dbt
Lead discovery sessions and technical workshops with the client’s data engineering teams
Document architecture, pipelines, and operational processes
Conduct architecture walkthrough sessions during knowledge transfer phases
Define standards for CI/CD, monitoring frameworks, and data quality validation
Establish schema management and governance best practices
Optimize Snowflake compute usage and platform performance
Design scalable orchestration strategies for Airflow pipelines
Improve platform reliability, monitoring, and operational observability
Required Skills & Qualifications:
Advanced / fluent English
10+ years of experience in Data Engineering or Data Architecture
Strong experience designing and implementing modern data platforms
Expert-level experience with Snowflake
Strong experience implementing dbt transformation frameworks
Advanced SQL modeling and performance optimization
Strong experience with Apache Airflow orchestration
Strong Python programming skills
Experience designing: ELT pipelines, Data warehouse architectures, Transformation frameworks, Large-scale data pipelines
Experience working in cloud environments (AWS preferred)
Nice to Have
Snowflake certification
Experience leading data platform migrations or modernization initiatives
Experience implementing Medallion architecture patterns
Experience defining data governance frameworks
Experience working with distributed or global engineering teams
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.