Databricks Data Engineer: Lakehouse AI Solutions

NTT Ltd.

Greater London

Hybrid

GBP 70,000 - 110,000

Full time

12 days ago

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Job summary

NTT DATA, a global technology services leader, is seeking a Databricks Data Engineer to design and optimize scalable data pipelines and lakehouse architectures. You will enable advanced analytics and AI use cases on the Databricks platform, delivering secure, well-governed data products for clients.

The role requires strong Python/SQL skills, cloud experience (AWS/Azure/GCP), and hands-on expertise across the data lifecycle.

Qualifications

  • Minimum 5–8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years working with Databricks.
  • University degree required; preferred MSc/PhD in a data-related field.
  • Databricks certifications (Data Engineer Professional) highly desirable.

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

Skills

Databricks data engineering
Client-facing collaboration
Data lifecycle expertise
Problem solving & communication
Team leadership/mentoring

Education

Bachelor’s degree in Computer Science or related field
BSc/MSc in CS/Data Engineering or related field
Databricks Data Engineer Certification (Professional)

Tools

Databricks platform (Spark/PySpark/Scala)
Delta Lake
Unity Catalog
MLflow
DBT
Matillion
Talend
GitHub/Bitbucket

Job description

NTT DATA, a global technology services leader, is seeking a Databricks Data Engineer to design and optimize scalable data pipelines and lakehouse architectures. You will enable advanced analytics and AI use cases on the Databricks platform, delivering secure, well-governed data products for clients.

The role requires strong Python/SQL skills, cloud experience (AWS/Azure/GCP), and hands-on expertise across the data lifecycle.

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