Data Engineer

Role Overview

Join our digital revolution in NatWest Digital X. We aim to make digital experiences which are effortless and secure, organized around three principles: engineer, protect, and operate. We are seeking a Data Engineer at the associate level to use technical expertise to collaborate and build effortless, digital-first customer experiences. You will simplify the bank by developing innovative data-driven solutions, ensuring customer and bank data safety, and actively participating in the data engineering community.

Responsibilities

• Play a key role in driving value for customers by building data solutions.
• Carry out data engineering tasks to build, maintain, test, and optimize a scalable data architecture.
• Perform data extractions, transform data to make it usable for data analysts and scientists, and load data into data platforms.
• Develop comprehensive knowledge of the bank’s data structures and metrics, advocating change where needed for product development.
• Practice DevOps adoption in the delivery of data engineering, proactively performing root cause analysis and resolving issues.
• Collaborate closely with core technology and architecture teams to build data knowledge and data solutions.
• Develop a clear understanding of data platform cost levers to build cost-effective and strategic solutions.
• Source new data using the most appropriate tooling and integrate it into the overall solution.

Requirements

To be successful, you will need a good understanding of data usage and dependencies with wider teams and the end customer, as well as experience extracting value and features from large-scale data. You must demonstrate:

• At least four to eight years of experience in SQL (RDBMS and NoSQL), data warehousing, data modeling, and designing ETL/ELT frameworks for efficient data processing and integration.
• Experience in building and managing cloud-based data pipelines for data migration, storage, and transformation, leveraging automation and orchestration tools to streamline workflows.
• Proficiency in Python for data engineering and automation, with a solid understanding of data governance, security, and best practices for managing enterprise data assets.
• Good knowledge of modern code development practices.
• Strong communication skills with the ability to proactively engage with a wide range of stakeholders.