Sr. Data Engineer (SDE) works closely with other Data Leads, Delivery Leads and Chapter head and help drive the Data Management and Analytics vision and strategy to deliver common, secure and consistent data capabilities across the EmiratesNBD Group. This role will involve strategic initiatives and reports into Head of Data Engineering Chapter and will manage the Data engineering, architecture and design of related approaches, tools and technologies.
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.
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.

KEY REQUIREMENTS:

• Master or Bachelor’s degree in computer science, information systems management or related field
• More than 8+ years of experience in information technology, with 3+ years spent in data engineering, architecture and 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 Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival
• Define workload migration strategies using appropriate tools
• Drive delivery in a matrixed environment working with various internal IT partners
• Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously
• Must be able to work independently and have skills in planning, strategy, estimation, scheduling,
• Strong problem solving, influencing, communication, and presentation skills, self-starter
• Strong hands-on expertise in programming on PySpark
• Experience with data processing frameworks and platforms (Hadoop, Presto, Tez, Hive, Spark etc.)
• Exposure to BI tools and reporting software (e.g. MS PowerBI and Tableau)Business Acumens
• Organization leadership skillsCoaching and mentoring
• Excellent analytical skills
• Demonstrate critical and systems of thinking ability.
• Ability to negotiate and influenceDisciplined, organized Flexibility / Adaptability Visionary
• Performance driven
  

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• Good understanding of source systems data structures, data retentions policies and data partitioning for modeling raw data vault structures
• Implement data quality and business rule
• Assist in modelling & take full ownership to implement the movement of data from source systems to staging data layer, raw data vault, transformed data vault and dimensional data layer
• Drive data reusability, reduce duplicity of data, minimizing adverse impact to performance
• 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
• Develop strategy to align with external regulatory requirements
• 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 data model to standardize data exchange between systems and with various architects to enforce the same