Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

NTT DATA
Glasgow
1 week ago
Create job alert

Req ID: 333370

Competitive salary | UK/Glasgow: hybrid working model (2-3 days on site)

At NTT DATA, we know that with the right people on board, anything is possible. The quality, integrity, and commitment of our employees are key factors in our company’s growth, market presence and our ability to help our clients stay a step ahead of the competition. By hiring the best people and helping them grow both professionally and personally, we ensure a bright future for NTT DATA and for the people who work here.

NTT DATA is currently looking for a Data Engineer for our growing team in the UK.

Overview:

NTT DATA is seeking a highly skilled Data Engineer with over 4+ years of experience to join our team to help a strategic banking client in various data transformation activities.

Key Responsibilities:

  • Collaborating with cross-functional teams to understand data requirements, and design efficient, scalable, and reliable ETL processes using Python and Databricks
  • Developing and deploying ETL jobs that extract data from various sources, transforming them to meet business needs.
  • Taking ownership of the end-to-end engineering lifecycle, including data extraction, cleansing, transformation, and loading, ensuring accuracy and consistency.
  • Creating and managing data pipelines, ensuring proper error handling, monitoring and performance optimizations
  • Working in an agile environment, participating in sprint planning, daily stand-ups, and retrospectives.
  • Conducting code reviews, providing constructive feedback, and enforcing coding standards to maintain a high quality.
  • Developing and maintaining tooling and automation scripts to streamline repetitive tasks.
  • Implementing unit, integration, and other testing methodologies to ensure the reliability of the ETL processes
  • Utilizing REST APIs and other integration techniques to connect various data sources
  • Maintaining documentation, including data flow diagrams, technical specifications, and processes.
  • Designing and implementing tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack.
  • Collaborate seamlessly across diverse technical stacks, including Databricks, Snowflake, etc.
  • Developing various components in Python as part of a unified data pipeline framework.
  • Contributing towards the establishment of best practices for the optimal and efficient usage of data across various on-prem and cloud platforms.
  • Assisting with the testing and deployment of our data pipeline framework utilizing standard testing frameworks and CI/CD tooling.
  • Monitoring the performance of queries and data loads and perform tuning as necessary.
  • Providing assistance and guidance during QA & UAT phases to quickly confirm the validity of potential issues and to determine the root cause and best resolution of verified issues.
  • Adhere to Agile practices throughout the solution development process.
  • Design, build, and deploy databases and data stores to support organizational requirements.

Skills / Qualifications:

  • 4+ years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc.
  • 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines
  • 3+ years of proficiency in working with Snowflake or similar cloud-based data warehousing solutions
  • 3+ years of experience in data development and solutions in highly complex data environments with large data volumes.
  • Solid understanding of ETL principles, data modelling, data warehousing concepts, and data integration best practices
  • Familiarity with agile methodologies and the ability to work collaboratively in a fast-paced, dynamic environment.
  • Experience with code versioning tools (e.g., Git)
  • Knowledge of Linux operating systems
  • Familiarity with REST APIs and integration techniques
  • Familiarity with data visualization tools and libraries (e.g. Power BI)
  • Background in database administration or performance tuning
  • Familiarity with data orchestration tools, such as Apache Airflow
  • Previous exposure to big data technologies (e.g. Hadoop, Spark) for large data processing
  • Strong analytical skills, including a thorough understanding of how to interpret customer business requirements and translate them into technical designs and solutions.
  • Strong communication skills both verbal and written. Capable of collaborating effectively across a variety of IT and Business groups, across regions, roles and able to interact effectively with all levels.
  • Self-starter. Proven ability to manage multiple, concurrent projects with minimal supervision. Can manage a complex ever changing priority list and resolve conflicts to competing priorities.
  • Strong problem-solving skills. Ability to identify where focus is needed and bring clarity to business objectives, requirements, and priorities.

Preferred Qualifications

  • Experience in financial services
  • Knowledge of regulatory requirements in the financial industry

Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).

Benefits

Our people are the most critical component of our long-term success and their health and wellbeing are our priority. You will enjoy a comprehensive, locally competitive benefits package.

About NTT DATA

NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies.Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us atus.nttdata.com

NTT DATA endeavors to make https://us.nttdata.comaccessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

#LI-EMEA
#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Engineering Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data engineering hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise reliable pipelines, modern lakehouse/streaming stacks, data contracts & governance, observability, performance/cost discipline & measurable business outcomes. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for platform‑oriented DEs, analytics engineers, streaming specialists, data reliability engineers, DEs supporting AI/ML platforms & data product managers. Who this is for: Data engineers, analytics engineers, streaming engineers, data reliability/SRE, data platform engineers, data product owners, ML/feature‑store engineers & SQL/ELT specialists targeting roles in the UK.

Why Data Engineering Careers in the UK Are Becoming More Multidisciplinary

For many years, data engineering in the UK meant designing pipelines, moving data between systems, and ensuring analysts had what they needed. Today, the field is expanding. With cloud platforms, machine learning, real-time analytics and the explosion of sensitive personal data, employers expect data engineers to do much more. Modern data engineering is no longer just about code and storage. It requires legal awareness, ethical judgement, psychological insight, linguistic clarity and human-centred design. These disciplines shape how data is collected, processed, explained and trusted. In this article, we’ll explore why data engineering careers in the UK are becoming more multidisciplinary, how law, ethics, psychology, linguistics & design now influence job descriptions, and what job-seekers & employers must do to thrive.

Data Engineering Team Structures Explained: Who Does What in a Modern Data Engineering Department

Data has become the lifeblood of modern organisations. Every sector in the UK—finance, healthcare, retail, government, technology—is increasingly relying on insights derived from data to drive decisions, deliver products, and improve operations. But raw data on its own isn’t enough. To make data useful, reliable, secure, and scalable, companies must build strong data engineering teams. If you’re recruiting for data engineering or seeking a role, understanding the structure of such a team and who does what is essential. This article breaks down the typical roles in a modern data engineering department, how they collaborate, required skills and qualifications, expected UK salaries, common challenges, and advice on structuring and growing a data engineering team.