Hadoop Data Engineer/ Senior Consultant Specialist

Some careers shine brighter than others.

If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of Senior Consultant Specialist

In this role  will be responsible for the below:

• The Senior Data Engineer will be responsible for designing, building, and managing the data infrastructure and data pipeline processes for the bank. This role involves leading a team of data engineers, working closely with data scientists, analysts, and IT professionals to ensure data is accessible, reliable, and secure. The ideal candidate will have a strong background in data engineering, excellent leadership skills, and a thorough understanding of the banking industry's data requirements.
• Leadership and Team Management . Lead, mentor, and develop a team of data engineers.
• Establish best practices for data engineering and ensure team adherence.
• Coordinate with other IT teams, business units, and stakeholders.
• Data Pipelines Integration and Management:
• Design and implement scalable data architectures to support the bank's data needs.
• Develop and maintain ETL (Extract, Transform, Load) processes.
•  Ensure the data infrastructure is reliable, scalable, and secure.
• Oversee the integration of diverse data sources into a cohesive data platform.
• Ensure data quality, data governance, and compliance with regulatory requirements.
• Develop and enforce data security policies and procedures.
• Monitor and optimize data pipeline performance.
• Troubleshoot and resolve data-related issues promptly.
• Implement monitoring and alerting systems for data processes