Databricks Lead Engineer - NTT DATA

OpenTalent; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

NTT DATA in the UK is looking for an experienced data engineer to help deliver scalable, secure data solutions on Databricks and cloud-native platforms. You’ll build batch and streaming pipelines, shape data models, and implement lakehouse architectures to meet client needs.

You’ll partner with data architects, analysts and stakeholders to ensure governance, quality and secure data flows across projects, applying best practices and delivery excellence.

Qualifications

• Proven experience in data engineering and pipeline development on Databricks and cloud-native platforms.
• Collaborate effectively in client-facing environments with strong consulting values.
• Hands-on expertise across ingestion, transformation, modelling, governance, and consumption.
• Strong problem-solving, analytical and communication skills.
• Experience leading or mentoring teams of engineers to deliver scalable data solutions.
• Deep expertise with Databricks platform (Spark/PySpark/Scala, Delta Lake, Unity Catalog, MLflow).
• Proficiency in ETL/ELT tools such as DBT, Matillion, Talend.
• Strong SQL and Python 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 (GitHub, Bitbucket) and CI/CD pipelines.
• Understanding of data governance, security, and compliance frameworks.
• Exposure to AI/ML workloads desirable.
• Education: University degree required. Preferred: BSc/MSc in Computer Science, Data Engineering, or related field
• Databricks certifications (Data Engineer Professional) highly desirable.
• 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.

Responsibilities

• Engage clients and deliver data engineering solutions.
• Develop batch and streaming data pipelines.
• Design and implement Databricks lakehouse architectures.
• Model and optimise data using Delta Lake and Medallion architecture.
• Collaborate across teams and promote best practices.
• Ensure quality, governance and security of data assets.
• Collaborate with solution architects on design.
• Work with engineers, developers, ML engineers and analysts.
• Engage stakeholders up to leadership in analytics.

Skills

Databricks

Delta Lake

SQL

Python

ETL/ELT

Data Modelling

Cloud platforms

Git & CI/CD

Data Governance

Communication

Education

University degree

BSc in Computer Science

MSc in Data Engineering

Tools

Databricks

DBT

Matillion

Talend

GitHub

Job description

Make an impact with NTT DATA Join 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 DATA

• 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
• 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:

• 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.
• 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 (GitHub, Bitbucket) and CI/CD pipelines.
• Understanding of data governance, security, and compliance frameworks.
• Exposure to AI/ML workloads desirable.
• Experience: Minimum 5-8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years working with Databricks.
• Education: University degree required.
• Preferred: BSc/MSc in Computer Science, Data Engineering, or related field
• Databricks certifications (Data Engineer Professional) highly desirable.
• 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.