Lead Data Architect - Qualified Pipeline

Location: Remote, US based

Position @type: TBD

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

Data Meaning

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Lead Data Architect - Qualified Pipeline