Lead Data Architect

Accountabilities: As a Lead Data Architect, you will lead the assessment, design, and modernization of enterprise data platforms while establishing best practices for scalable data engineering and architecture. You will work closely with technical teams to define future-state solutions, improve platform capabilities, and ensure long-term reliability and governance.

Lead architecture assessments and document existing data platforms, including Snowflake, Airflow, and cloud-based environments.

Design future-state data platform architectures using modern ELT principles and dbt transformation frameworks.

Define standards for data modeling, pipeline architecture, transformation processes, governance, and data quality.

Guide the migration of existing SQL-based transformations into scalable dbt models.

Establish architectural patterns for staging layers, intermediate layers, and data marts.

Implement automated testing strategies and data validation frameworks within dbt environments.

Lead technical workshops, discovery sessions, and architecture walkthroughs with data engineering teams.

Document data architectures, pipelines, operational processes, and technical standards.

Define best practices for CI/CD processes, monitoring frameworks, schema management, and platform observability.

Optimize Snowflake performance, compute utilization, and overall platform scalability.

Design reliable orchestration strategies for Airflow pipelines and improve operational efficiency.

Requirements:

The ideal candidate is a highly experienced data architecture professional with a strong background in designing modern data platforms and leading complex modernization initiatives. You should combine deep technical expertise with strong communication skills and the ability to guide engineering teams through large-scale transformations.

10+ years of experience in Data Engineering, Data Architecture, or related technical roles.

Advanced or fluent English communication skills.

Extensive experience designing and implementing modern data platforms.

Expert-level knowledge of Snowflake architecture, development, and optimization.

Strong experience implementing dbt transformation frameworks and modern ELT pipelines.

Advanced SQL skills, including data modeling and performance optimization.

Strong experience with Apache Airflow orchestration.

Proficiency in Python programming for data engineering solutions.

Experience designing enterprise data warehouses, large-scale data pipelines, and transformation frameworks.

Experience working with cloud environments, preferably AWS.

Strong understanding of data governance, quality frameworks, and scalable architecture principles.

Experience collaborating with distributed or global engineering teams.

Snowflake certification is a plus.

Experience leading data platform migrations, modernization programs, or implementing Medallion architecture patterns is highly valued.

Benefits:

Competitive compensation package of $190,000 base salary plus bonus .

Fully remote position for candidates based in the United States.

Opportunity to lead impactful enterprise data modernization initiatives.

Work with innovative cloud data technologies and modern architecture frameworks.

Collaborative environment with distributed global teams.

Opportunity for professional growth through challenging technical projects.

Ability to influence data strategy, governance, and engineering best practices.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

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