Data Architect, AVP

Barclays - Hanover, NJ

Full-time - Senior

Remote - Hanover, NJ

Credit Intermediation and Related Activities

About the position

The Data Architect, AVP role at Barclays involves developing and implementing data management procedures, ensuring high-quality data and reduced redundancy, and translating business needs into effective data models. The position focuses on building and maintaining systems for data collection, storage, processing, and analysis, including data pipelines, data warehouses, and data lakes. The role also includes collaboration with data scientists to deploy machine learning models and establishing data governance frameworks.

Responsibilities

• Develop and implement procedures covering data management, model development, testing, technical implementation, model execution, and monitoring.
• Ensure complex business requirements are accurately captured, documented, communicated, and understood by the business.
• Translate business needs into conceptual, logical, and physical data models supporting long-term solutions ensuring high-quality data and reduced redundancy.
• Assess the quality of data and inputs for data model development and provide recommendations to improve data quality at the source.
• Perform data analysis including data profiling and data validation.
• Develop and manage BI dependency plan, job scheduling, and cycle management.
• Work with data designer and ETL architect.
• Resolve semantic discrepancies in data definitions that arise among multiple sources and projects.
• Create and implement Data Governance framework that meets data objectives.
• Establish and ensure to follow Data Quality Governance standards across various applications.
• Support proactive and reactive Change Management activities for reference data values and the structure/use of master data and metadata.
• Identify stakeholders and specific value propositions for solving data-related issues.
• Develop scripts for load strategies, backup, and recovery to ensure system availability 24/7.
• Develop ETL and PL/SQL packages, conduct Unit testing, performance testing, and coordinate production deployment, and resolve post-implementation issues.

Requirements

• Senior level experience in SQL and PL/SQL.
• Experience in machine learning and ETL processes.
• Strong skills in unit testing and performance testing.
• Proven ability to develop and manage data architectures and pipelines.

Nice-to-haves

• Experience with data governance frameworks.
• Familiarity with data profiling and validation techniques.
• Knowledge of data quality governance standards.

Benefits

• Employee Referral Program incentives
• Telecommuting options