Senior Data Engineer

This role is based in Chennai, India.

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 Emirates

NBD 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.

Roles & 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 optimization

Drive data reusability, reduce duplicity of data, minimizing adverse impact to performance
Cloudera Data Platform (CDP)
Hadoop ecosystem
Apache Iceberg
Apache Doris
Kubernetes/Open Shift
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 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 datamodel to standardize data exchange between systems and with various architects to enforce the same

Required Qualifications:

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 Py Spark

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, scheduling,
Business Acumens
Organization leadership skills
Coaching and mentoring
Excellent analytical skills
Demonstrate critical and systems of thinking ability.
Ability to negotiate and influence
Disciplined, organized
Flexibility / Adaptability
Visionary
Performance driven