Sr Data Architect

Capco•Washington, DC

5h•Onsite

About The Position

We are seeking an experienced, detail-oriented Senior Data Architect to join a cross-functional Agile team. The role designs, builds, and maintains scalable, high-performing cloud data platforms using Snowflake. The architect defines how data is stored, integrated, secured, and used across the organization, aligning data architecture with business objectives and supporting analytics, reporting, and strategic decision-making. Working with data engineers, backend and frontend developers, product managers, and business stakeholders, the Senior Data Architect develops enterprise data models and architecture solutions for application development and business intelligence. The role also supports enterprise-wide data transformation initiatives and establishes architectural best practices using modern cloud technologies.

Requirements

Extensive experience designing and implementing enterprise-level data platforms and data warehouse architectures.
In-depth knowledge of Snowflake architecture, data modelling, performance optimization, and cost management.
Experience with dimensional modelling techniques, including Star Schema, Snowflake Schema, and Data Vault 2.0.
Advanced SQL skills, including query optimization, data transformation, and complex data modelling.
Understanding of enterprise data warehousing, analytics architecture, and data integration patterns.
Hands-on experience with dbt for data transformation, modelling, 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 with a strategic, enterprise-wide perspective.
Experience providing technical guidance, mentoring engineers, and reviewing architecture designs.
Effective communication and collaboration skills, with 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.
Optimize Snowflake platforms for scalability, reliability, performance, and cost efficiency.
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 meet 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.
Collaborate with engineering, analytics, product, and business teams to translate business requirements into technical solutions.
Design and support AWS cloud-based data architecture aligned with enterprise technology strategies.