Data Engineer- Asset Management

1 week ago

Knutsford Cheshire, United Kingdom Ubique Systems Full time

A leading UK bank is seeking a skilled Data Engineer to support the Product Lifecycle Catalogue (hardware and software) underpinning IT Asset Management (ITAM) in ServiceNow. This role is driven by regulatory requirements and involves close collaboration with the Solution Architect and Data Analytics teams. The Data Engineer will be responsible for building and maintaining data systems that ensure data accuracy, accessibility, and security.

Data System Development: Design, build, and maintain robust data systems, including data pipelines, data warehouses, and data lakes, to efficiently collect, store, process, and analyze large volumes of data.
Data Governance: Implement and enforce data governance practices, ensuring data integrity, compliance with regulatory standards, and adherence to the bank's data policies.
Collaboration: Work closely with the Solution Architect and Data Analytics teams to align data engineering efforts with broader IT and business objectives.
Machine Learning & Data Mining: Apply machine learning techniques and data mining processes to enhance data processing capabilities and extract valuable insights.
Ensure that all data systems are developed with secure coding practices to protect sensitive information and comply with security protocols.
Change & Transformation: Support change and transformation initiatives by developing scalable and adaptable data solutions that can evolve with the bank's needs.
Database Management: Design and manage database structures that support efficient data storage, retrieval, and analysis.
Contribute to the development of data strategies that align with the bank’s long-term goals and digital transformation efforts.
Risk & Controls: Identify potential risks in data processes and implement controls to mitigate these risks, ensuring compliance with internal and external regulations.
Engage with cross-functional teams to ensure that data solutions are fully integrated and support business processes effectively.

DevOps: Experience with DevOps practices to support continuous integration and deployment of data systems.
Data Governance: Strong knowledge of data governance frameworks and their application in a financial environment.
Requirements Analysis: Ability to conduct detailed requirements analysis to inform data system design and development.
Machine Learning: Proficiency in applying machine learning techniques to data processing and analysis.
Data Mining: Experience with data mining techniques to extract valuable insights from large datasets.
Strategic Thinking: Ability to align data engineering efforts with the bank’s strategic objectives.
Data Warehousing (DW): Expertise in designing and managing data warehouses that support large-scale data analysis.
Change & Transformation: Experience in supporting change initiatives through the development of flexible and scalable data solutions.
Database Structures: Strong skills in designing and managing database structures that ensure efficient data storage and retrieval.
Secure Coding Practices: Proficiency in secure coding practices to protect sensitive data.
Risk & Controls: Knowledge of risk management and control measures specific to data systems in a financial context.
Data Engineering: Proven experience in data engineering, with a focus on building and maintaining data systems in a complex, regulated environment.

This role is critical for ensuring that the bank's data systems are robust, secure, and aligned with regulatory requirements, supporting the bank’s strategic goals and digital transformation initiatives.

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