Sr Data Architect

Capco•Washington DC, WA

4d•Onsite

About The Position

The Senior Data Architect will join a cross-functional Agile team to design, build, and maintain scalable, high-performing cloud data platforms using Snowflake. The role defines how data is stored, integrated, secured, and used across the organization, ensuring the data architecture aligns with business objectives and supports analytics, reporting, and strategic decision-making. The architect works with data engineers, backend and frontend developers, product managers, and business stakeholders to develop enterprise data models and architecture solutions for application development and business intelligence. The position also contributes to architectural best practices and enterprise-wide data transformation initiatives.

Requirements

Extensive experience designing and implementing enterprise-level data platforms and data warehouse architectures.
In-depth knowledge of Snowflake architecture, data modeling, performance optimization, and cost management.
Experience with dimensional modeling techniques, including Star Schema, Snowflake Schema, and Data Vault 2.0.
Advanced SQL skills, including query optimization, data transformation, and complex data modeling.
Understanding of enterprise data warehousing, analytics architecture, and data integration patterns.
Hands-on experience with dbt for data transformation, modeling, and production data pipelines.
Experience with workflow orchestration and data integration tools such as Apache Airflow, Dagster, Kafka, or similar technologies.
Experience designing and implementing ETL/ELT pipelines and data ingestion frameworks.
Knowledge of AWS cloud services and cloud-based data platform architecture.
Experience integrating Snowflake with data engineering, orchestration, and business intelligence tools such as Sigma and Qlik.
Understanding of enterprise data governance frameworks, data quality standards, and regulatory compliance requirements.
Experience implementing data security controls, access management, and data protection policies.
Knowledge of performance tuning, workload optimization, and cost management within cloud data platforms.
Ability to develop and maintain architectural documentation, design standards, and technical best practices.
Ability to approach complex technical challenges from a strategic, enterprise-wide perspective.
Experience providing technical guidance, mentoring engineers, and reviewing architecture designs.
Effective communication and collaboration skills, including experience working across engineering, analytics, and business teams.
Experience working in Agile/Scrum environments and managing delivery activities using Jira.
Bachelor's or master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline, or equivalent practical experience.
Typically 7–10+ years of relevant experience in data engineering, data architecture, or analytics.
Demonstrated experience in a data architecture or technical leadership role.
Experience building, deploying, and maintaining scalable dbt projects in production environments using Snowflake and Airflow.
Experience maintaining high standards of technical documentation, data quality, governance, and platform performance.

Nice To Haves

Snowflake and relevant cloud certifications are advantageous.

Responsibilities

Design and implement scalable, secure, high-performing enterprise data architecture using Snowflake and AWS.
Define and maintain enterprise data models, schemas, and architectural standards, including Star Schema, Snowflake Schema, and Data Vault 2.0.
Architect data ingestion, integration, and transformation strategies using ETL/ELT frameworks and tools such as dbt, Airflow, and Kafka.
Ensure the scalability, reliability, performance, and cost efficiency of Snowflake data platforms through architecture and optimization.
Establish data security, governance, and compliance standards, including access controls, role-based permissions, data masking, and data protection policies.
Evaluate, select, and integrate data engineering, orchestration, and analytics tools to support enterprise requirements.
Provide architectural guidance to data engineering teams, review technical designs, and promote consistent engineering standards.
Establish and maintain architectural best practices, technical documentation, and data design standards.
Partner with engineering, analytics, product, and business teams to translate business requirements into technical solutions.
Design and support cloud-based data architecture across AWS in alignment with enterprise technology strategies.
Build, deploy, and maintain scalable dbt projects in production environments using Snowflake and Airflow.
Maintain standards for technical documentation, data quality, governance, and platform performance.
Manage delivery activities using Jira in Agile/Scrum environments.