Primary Objective of the role:

• Manage a team of data engineers (both full-time associates and/or third-party resources)
• Responsible for verifying requirements, defining architecture, develop an implementation plan, provide thought leadership for all data solutions, including designing data solutions
• Analyzes and confirms the integrity of source data to be evaluated
• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using big data technologies

Key Responsibilities:

• Lead Data Engineering Chapter for Group Analytics
• Gather and process raw data at scale.
• Design and develop data applications using selected tools and frameworks as required and requested.
• Read, extract, transform, stage and load data to selected tools and frameworks as required and requested.
• Collaborate with data stakeholders and stewards on the verification and the accuracy of the information collected.
• Provide technical lead to Data Owners and Stewards on data definition, data lineage changes by supporting intake process, performing impact analysis, and conducting domain specific profiling.
• Write, deploy and maintain software to build, integrate, manage, maintain, and quality-assure data, and responsible for deploying secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline
• Custom integration with various banking systems, data warehouses, and analytics systems.
• Setup of data-access or visualization tools for data scientists such as data science workbench
• Develop and implement analytics use case to yield business value from data and insight
• Extracts and transforms structured and unstructured big and small data to generate features, derive impactful insight, visualize information, and support impactful decision-making
• Design of data pipeline and implement data ingestion from end-to-end to Big Data repositories.
• Applies best practices in modular architecture, loosely coupled design, and agile development / continuous deployment software engineering principles
• Design and implement modern data pipelines to extract, clean and process data in batch and real-time from different data sources.
• Demonstrates efficiency through contributing to and applying bank-wide best practices in analytics and data
• Develops technical architecture for data applications and analytics platforms (together with relevant agile team)
• Human-centered design (together with digital team)
• Data Management & Data Governance for Big Data Platform

Requirements:

• Bachelor Degree - Any related field(s).
• 7+ years Data Warehouse/Data Lake Architecture and Development
• 5+ years Data Modeling & Architecture
• Experience on Cloud Solutions (both AWS & Azure)
• ETL/ELT Pipelines
• Non-Relational Database experience (Document DB, Graph DB, etc.)
• API/Embedded experience
• Expertise in SQL, Python & Scala
• Data preparation Experience
• 3 years’ experience in analytics related roles (banking experience is a plus)

• Data Warehouse
• Data Engineering