Databricks Data Engineer

Make an impact with NTT DATAJoin a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive.

Your day at NTT DATAWe are seeking a highly skilled Databricks Data Engineer to join our Data & AI practice.  The successful candidate will have deep expertise in building scalable data pipelines, optimizing Lakehouse architectures and enabling advanced analytics and AI use cases on the Databricks platform.  This role is critical in building and optimizing modern data ecosystems that enable data-driven decision making, advanced analytics, and AI capabilities for our clients.

As a trusted practitioner, you will design and implement robust ETL/ELT workflows, integrate real-time and batch data sources, and enable secure, well-governed data products and pipelines.  You will thrive in a collaborative, client-facing environment, with a passion for solving complex data challenges, driving innovation and ensuring the seamless delivery of data solutions..Looking ahead to future opportunities. As our business continues to grow, we are building a pipeline of exceptional talent for upcoming positions across the UK.

This advertisement is intended to identify and engage candidates in advance of specific vacancies becoming available. We encourage you to apply if you would like to be considered for future opportunities that match your expertise

Primary Responsibilities
• Client Engagement & Delivery
• Data Pipeline Development (Batch and Streaming)
• Databricks & Lakehouse Architectures
• Data Modelling & Optimisation (Delta Lake, Medallion architecture)
• Collaboration & Best Practices
• Quality, Governance & Security Business Relationships
• Solution Architects
• Data Engineers, Developers, ML Engineers, and Analysts
• Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadership

To thrive in this role, you need to have:

Key Competencies
• Proven experience in data engineering and pipeline development on Databricks and cloud-native platforms.
• Strong consulting values with ability to collaborate effectively in client-facing environments.
• Hands-on expertise across the data lifecycle: ingestion, transformation, modelling, governance, and consumption.
• Strong problem-solving, analytical, and communication skills.
• Experience leading or mentoring teams of engineers to deliver high-quality scalable data solutions.

Technical Expertise
• Deep expertise with the Databricks platform (Spark/PySpark/Scala, Delta Lake, Unity Catalog, MLflow).
• Proficiency in ETL/ELT tools such as DBT, Matillion, Talend, or equivalent.
• Strong SQL and Python (or equivalent language) skills for data manipulation and automation.
• Hands-on experience with cloud platforms (AWS, Azure, GCP).
• Familiarity with Databricks Workflows and other orchestration tools.
• Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).
• Familiarity with medallion architectures, data lakehouse principles and distributed data processing.
• Experience with version control tools (Git Hub, Bitbucket) and CI/CD pipelines.
• Understanding of data governance, security, and compliance frameworks.
• Exposure to AI/ML workloads desirable. Experience, Qualifications, and Education
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Experience:

Minimum 5–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years working with Databricks.
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Education:

University degree required.
• Preferred: BSc/MSc in Computer Science, Data Engineering, or related field
• Databricks certifications (Data Engineer Professional) highly desirable.

Measures of Success
• Delivery of high-performing, scalable, and secure data pipelines aligned to client requirements.
• High client satisfaction and successful adoption of Databricks-based solutions.
• Demonstrated ability to innovate and improve data engineering practices.
• Contribution to the growth of the practice through reusable assets, accelerators, and technical leadership. Workplace type:
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