Data Modeler / Architect

Purpose of the role

To design, implement, and maintain conceptual, Logical and Physical data models that meet business data/process and technology requirements, by using designs and data strategies across a wide selection of platforms. 

Accountabilities

• Analysis and documentation of business requirements to translate them into data models aligned with organisational goals.
• Development and maintenance of data dictionaries and glossaries to define data elements and their usage.
• Analysis and monitoring of data usage patterns to identify opportunities for data optimisation and improvement, in partnership with the Data Base Administrator.
• Strategic architecture definition and product selection.
• Production of logical designs in relevant subject area (technical, data, operational), showing for example: processes, objects, data flows, inputs, stored data and outputs. Identifying common components.
• Implementation of architectures and Identification, ownership and resolution of design related issues.
• Definition and documentation of data architectures standards, principles and strategies.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join us as a Data Modeller in Barclays, responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences.

To be successful as a Data Modeller you should have experience with: -

• Data Modelling Techniques

  
  
  

  • Conceptual, Logical, and Physical data modelling

    
    
    

  • Normalization / Denormalization

    
    
    

  • Dimensional modelling (Star/Snowflake schema)

    
    
    

  • Entity-Relationship (ER) modelling

    
    
    

• Data Modelling Tools

  
  
  

  • ER/Studio

    
    
    

  • Erwin Data Modeler

    
    
    

• Database Systems

  
  
  

  • Relational: Oracle, SQL Server, PostgreSQL, MySQL

    
    
    

  • Columnar: Amazon Redshift, Snowflake

    
    
    

  • NoSQL: MongoDB, Cassandra (for some use cases)

    
    
    

• SQL and Scripting

  
  
  

  • Advanced SQL (DDL, DML, performance tuning)

    
    
    

  • PL/SQL or T-SQL

    
    
    

  • Python or Shell scripting for data validation and automation

    
    
    

• Data Warehousing & ETL

  
  
  

  • Data warehousing concepts (Inmon, Kimball)

    
    
    

  • ETL tools: Informatica etc

    
    
    

• Cloud Platforms (increasingly common)

  
  
  

  • AWS (especially S3, Redshift, Glue)

    
    
    

  • Lake formation / Data Lake implementation 

    
    
    

• Investment Banking Data Concepts

  
  
  

  • Domains such as Deal, CRM, Instruments (equities, bonds) etc

    
    
    

  • Analytical and transactional data

    
    
    

  • Reference data (e.g., security master, client reference, legal entities)

    
    
    

• Market Data Vendors

  
  
  

  • Understanding of identifiers: ISIN, CUSIP, SEDOL, RIC

    
    
    

  • Familiarity with Bloomberg, FactSet, Refinitiv, Dealogic, etc.

    
    
    

• Data Governance & Lineage

  
  
  

  • Metadata management

    
    
    

  • Business glossary

    
    
    

  • Experience with tooling- DBT, Snowflake, Databricks, Immuta, Alation, Informatica, colibra etc

    
    
    

• Requirements Gathering

  
  
  

  • Working with business analysts, product managers, and stakeholders

    
    
    

  • Translating business requirements into data models

    
    
    

• Data Quality & Validation

  
  
  

  • Profiling data

    
    
    

  • Designing controls for accuracy, completeness, and consistency

    
    
    

• Performance Optimization

  
  
  

  • Indexing strategy

    
    
    

  • Partitioning, clustering

    
    
    

  • Query tuning for large datasets

    
    
    

Some other highly valued skills may include: -

• Stakeholder Communication

  
  
  

  • Explaining complex data structures to non-technical stakeholders

    
    
    

  • Cross-functional collaboration with engineering, business, and compliance teams

    
    
    

• Documentation

  
  
  

  • Creating and maintaining model dictionaries, lineage diagrams, etc.

    
    
    

• Agile/Project Management

  
  
  

  • Working in Agile/Scrum or Kanban teams

    
    
    

  • Using tools like JIRA or Confluence

    
    
    

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role is based in Pune.