Data Architect Data Design - AVP @ Barclays
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Job Details
Overview
Embark on a transformative journey as a Data Architect Data Design - AVP at Barclays, where you will design and maintain enterprise data models ensuring consistency, scalability, and compliance across global functions.
Key Responsibilities
- Design and implement conceptual, logical, and physical data models.
- Develop and maintain data dictionaries and glossaries.
- Analyze and optimize data usage patterns in collaboration with DBAs.
- Define strategic architecture and select appropriate products.
- Document data architecture standards, principles, and strategies.
Technical Skills Required
- Expertise in data modelling using Erwin, ER/Studio, or PowerDesigner.
- Advanced SQL and scripting with PL/SQL, T-SQL, Python, or Shell.
- Experience with data warehousing approaches and ETL tools like Informatica.
- Knowledge of relational, columnar, and NoSQL databases.
- Ability to design and implement cloud-native solutions on AWS or Azure.
Assistant Vice President (AVP) Expectations
Advise and influence decision making, set objectives, coach team members, and collaborate across global teams. Demonstrate leadership behaviours by listening, inspiring, aligning, and developing others while managing risk and strengthening controls.
Company Culture & Benefits
Barclays offers a competitive benefits package, including medical, dental, vision, 401(k), life insurance, paid leave and incentive awards. The role supports Barclays' values of Respect, Integrity, Service, Excellence and Stewardship.
Key skills/competency
Data modeling, Data architecture, SQL, ETL, Cloud, Governance, Compliance, Data warehousing, Risk management, Leadership
Location
This role is located in Whippany, New Jersey.
How to Get Hired at Barclays
🎯 Tips for Getting Hired
- Customize your resume: Highlight data modelling and SQL expertise.
- Research Barclays: Study their mission, values, and recent news.
- Showcase leadership: Detail team management and strategic projects.
- Prepare for technical rounds: Review data architecture, modelling tools, and ETL processes.