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VP, Data Architect, Group Consumer Banking and Big Data Analytics Technology, Technology and Ops

Singapore, Singapore | DBS Bank

  • Industry:
    Banking / Investment Banking
  • Position Type:
    Full-Time
  • Functions:
    Financial Services Professional
    IT / Information Technology
  • Experience:
    7-10 years
    10-12 years
    12-15 years
Job Description:
93 people have viewed this job

The position exists to cater to technology Data architecture for Big Data initiatives and projects planned on the BI & Analytics platform.

Establish best practices and guidelines for Data architecture / Data modelling.

Establish Data framework for Data Lake, Integration and Data marts.

Provide on-time Data model and design for initiatives and projects on Hadoop/Analytics platform.

Key Accountabilities 

Establish best practices and guidelines for Data architecture / Data modelling.

Establish Data framework for Data Lake, Integration and Data marts.

Establish best practices and guidelines to be followed by tech teams working on big data platform.

Provide on-time solutions and design for initiatives and projects on Hadoop/Analytics platform.

Provide on-time Data model and design for initiatives and projects on Hadoop/Analytics platform

Responsibilities 

Implementing Data Architecture/ Data modelling for data platform and Analytics.

Define and govern consumer banking logical model and data platform best practices and standards to include software development practices, design styles and software deployment.

Good knowledge on Data model physicalization.

Expert in selective denormalization of integrated layer based on Analytical needs.

Facilitate the discovery of entities, attributes, relationships, and business rules from the functional experts and the user community.

Develop and manage data models in Erwin and associated metadata for the enterprise.

Liaise & provide inputs to Data Management on enterprise level metadata management.

Define and enforce best practices for standard naming conventions and coding practices to ensure consistency of data models.

Responsible for defining the analytical presentation layers to ensure optimal data storage and to eliminate data redundancy.

Responsible for review of physical data models.

Responsible for the technical design of Analytics and big data systems including ETL, data transformations, reporting and analytics services.

Examine and evaluate Analytics & big data requirements for various business units across the organization.

Applying architecture and engineering concepts to design solutions that adhere to organization standards and cater for re-usability, scalability, maintainability and security. 

Contributing to analytics strategy and architecture that will align investments with the highest impact areas, while producing a suite of complementary models, tools and capabilities.

Working with cross-functional teams to discover and develop actionable, high-impact data analytics requirements and opportunity statements in a variety of core business areas.

Assessing tool implementations and architectures in the Analytics & Big data space, reviewing for gaps against business needs and industry best practices.

Contributing to business process design and re-engineering impacted areas.

Providing oversight to analytics and data warehousing activities in the team to ensure alignment of priorities, coordination of inter-related projects and ensuring success stories are leveraged.

Effectively communicating analyses, recommendations, status, and results to both business & technology leads.

Leading proof of concepts to create break through solutions, performing exploratory and targeted data analyses to drive iterative learning’s.

Requirements

At least 8 to 15 years of working experience, preferably in banking environments

Familiarity with key technologies and concepts, e.g. Hadoop, Hive, Spark, SparkR, Mahout, R , SAS, Phython/Java, Teradata are necessary

Candidate with experience in Analytics and big data architecture.

Familiarity with key technologies and concepts, SQL &Big Data.

Knowledge of products in Banking and Financial Services.

Ability to write clear documentation of procedures, and ability to write specifications for data models to be developed.

Detail-oriented and able to follow clear methodologies for troubleshooting and development.

Expert knowledge of data Architecture in financial service data models.

Expert knowledge of Erwin data modeler tool. Certifications would be a plus.

Expert in Data Analysis and Data Profiling.

Efficient in prioritising work and multi tasking. 


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