Sr Data Architect

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

• Job Summary
• 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.

Key Responsibilities

• 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.

Mandatory Qualifications & Skills

• Data Architecture & Modelling
• 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.

Data Engineering & Cloud Technologies

• 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.

Data Governance, Security & Performance

• 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.

Collaboration & Delivery

• 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.

Education & Experience

• 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.