Emirates NBD is a market leader across the MENAT (Middle East, North Africa and Türkiye) region with a presence in 13 countries, serving over 9 million customers. Emirates NBD is the leading financial services brand in the UAE with a Brand value of approximately USD 4 billion. 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 over half a million users, it continues to be the fastest-growing digital bank in the region.
The Senior Data Engineer 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.
This role requires an understanding of various data engineering, 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.
Key Responsibilities:
- Good understanding of source systems data structures, data retentions policies and data partitioning for modeling raw data vault structures
- Deep understanding of PySpark.
- Perform deep performance tuning including: Spark execution plan analysis, Partition optimization, Memory tuning, Shuffle optimization,
- Join strategy optimization, Data skew handling, Executor tuning, Serialization optimizationDrive data reusability, reduce duplicity of data, minimizing adverse impact to performance, Cloudera Data Platform (CDP), Hadoop ecosystem, Apache Iceberg, Apache Doris & Kubernetes/OpenShift.
- Participate in architecture discussions and contribute to enterprise-scale data engineering standards
- 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
- Drive best practices around performance engineering, CI/CD, testing, and operational excellence
- Develop data access matrix and ensure right information reaches the right people through secured channel
- 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
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Skills & Experience:
- 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
- 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 designing and developing reusable frameworks for enabling scalable and performant data pipelines
- 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 and scheduling
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There’s never been a better time to join Emirates NBD.
We’re one of the region’s most recognizable brands. We’re banking innovation leaders. We’re growing across both the UAE and our global offices. We offer a huge range of professional development opportunities to accelerate your career. It also goes without saying that we provide extremely competitive rewards, benefits and perks too, like our flexible work policy so you can work from home whenever it suits. At ENBD, we encourage interested candidates to review the key responsibilities and qualifications for each role and apply for positions that match their skills and capabilities.
