Lead Data Architect

Job Location
- Chennnai, India (On-Site)

Emirates NBD is a market leader across the MENAT (Middle East, North Africa and Türkiye) region with a presence in 13 countries, serving over 20 million customers. The Emirates NBD Group has a total of 853 branches and 4,213 ATMs / SDMs. Emirates NBD is the leading financial services brand in the UAE with a Brand value of USD 3.89 billion.
At the bank, we serve our customers and help them realize their financial objectives through a range of banking products and services including retail banking, corporate & institutional banking, Islamic banking, investment banking, private banking, asset management, global markets and treasury, and brokerage operations.
We are a key participant in the global digital banking industry, with 97% of all financial transactions and requests conducted outside of our branches. We also operate  Liv,  the lifestyle digital bank by Emirates NBD. With close to half a million users, it continues to be the fastest-growing digital bank in the region.

Job Role
- Lead Data Architect:
The unit is responsible for building, implementing and enforcing common structures and guidelines for architecture, development and testing practices in order to enable world-class solutions definition, delivery and build resilient, agile and secured technology landscape aligned with Emirates NBD business strategy.

The primary task is to drive and transform the data capabilities and enable a data-driven culture across the group and therefore work with other architects and platform teams to ensure data is managed as an asset in a centralized, standardized, and consistent manner in order to maintain consistency and quality, using mature technologies and emerging data practices.

Job Responsibilities:

Develop data architecture vision and standards in conjunction with business users and stewards
Outline short-term incremental solutions to achieve long-term objectives and an overall data management roadmap
Create data exchange standards to ensure reusability and a decoupled architecture
Create standards for data archival and purging
Identify and drive the implementation of secured data solutions
Develop data access matrix and ensure right information reaches the right people through secured channels
Identify and document critical data elements across source system of records
Define and document the data quality rules and standards
Assess and define data governance and stewardship maturity roadmap
Work with data engineers and source system experts to define the standards and principles for capturing lineage and data flow
Define data exception handling processes
Define standards for data pipeline scheduling and monitoring
Provide technical recommendations and engage with data engineers and BI leads throughout the solutioning and implementation lifecycle
Recommend effective solutions to develop high performant and scalable data pipelines
Work with source system expertise to understand the data domains and source to target mapping
Build and maintain canonical datamodel to standardize data exchange between systems and with various architects to enforce the same
Develop strategy to align with external regulatory requirements
This role requires an understanding of various data management and processing related technologies and choices, has a deep understanding of both SQL/No-SQL technologies, distributed computing framework, and techniques to make right tools and technology choices.

Job Requirements:

More than 8 years of experience in information technology, with 3 years spent in data architecture or technology solutions definitions and implementations.
Extensive experience in banking and financial services domain
Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions
Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security
Expertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification
Experiences in cloud native principals, designs and deployments.
Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments
Expertise in Data Mesh, Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival
Drive delivery in a matrixed environment working with various internal IT partners

Experience with data processing frameworks and platforms (Informatica, Hadoop, Presto, Tez, Hive, Spark etc.)
Production experience and expertise in Machine Learning architecture, Feature store and MLOps.
Machine Learning Architecture & Data architecture for large and complex organization and systems and implemented large scale end-to-end Analytics & Data solutions
Hands-on experience with…