Sr Data Architect

Location: Jersey City, NJ | Contract | Onsite | Payrate: $75/hr 

We are seeking an experienced and detail-oriented Senior Data Architect to join our cross-functional Agile team. In this role, you will design, build, and maintain scalable, high-performing cloud data platforms using Snowflake.

You will define how data is stored, integrated, secured, and used across the organisation, ensuring that data architecture aligns with business objectives and supports analytics, reporting, and strategic decision-making.

Working closely with data engineers, backend and frontend developers, product managers, and business stakeholders, you will develop enterprise data models and architecture solutions that support application development and business intelligence.

This role offers the opportunity to work with modern cloud technologies, establish architectural best practices, and contribute to enterprise-wide data transformation initiatives.

• →Enterprise Data Architecture: Design and implement scalable, secure, and high-performing enterprise data architecture using Snowflake and AWS cloud technologies.
• →Data Modelling and Design: Define and maintain enterprise data models, schemas, and architectural standards, including Star Schema, Snowflake Schema, and Data Vault 2.0 methodologies.
• →Data Integration and Transformation: Architect data ingestion, integration, and transformation strategies using ETL/ELT frameworks and technologies such as dbt, Airflow, Kafka, and related tools.
• →Performance and Cost Optimisation: Ensure the scalability, reliability, performance, and cost efficiency of Snowflake data platforms through effective architecture and optimisation techniques.
• →Data Governance and Security: Establish data security, governance, and compliance standards, including access controls, role-based permissions, data masking, and data protection policies.
• →Technology Selection and Integration: Evaluate, select, and integrate appropriate data engineering, orchestration, and analytics tools to support enterprise requirements.
• →Technical Guidance: Provide architectural guidance to data engineering teams, review technical designs, and promote consistent engineering standards.
• →Architecture Standards and Documentation: Establish and maintain architectural best practices, technical documentation, and data design standards.
• →Stakeholder Collaboration: Partner with engineering, analytics, product, and business teams to translate business requirements into effective technical solutions.
• →Cloud Architecture: Design and support cloud-based data architecture across AWS, ensuring alignment with enterprise technology strategies.

• Extensive experience designing and implementing enterprise-level data platforms and data warehouse architectures.
• In-depth knowledge of Snowflake architecture, including data modelling, performance optimisation, and cost management.
• Experience with dimensional modelling techniques, including Star Schema, Snowflake Schema, and Data Vault 2.0.
• Advanced SQL skills, including query optimisation, 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 maintaining 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 optimisation, 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.
• Snowflake and relevant cloud certifications are advantageous.