Databricks Data Engineer at NTT DATA, Inc.
At a glance
- Company
- NTT DATA, Inc.
- Location
- London, GB, United Kingdom
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this NTT DATA, Inc. job
- 🏢 This is NTT DATA, Inc.'s only job here right now
- 📊 12 Data Engineer jobs in the United Kingdom in the last 60 days see them
- 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
- 💡 No salary shown. Ask NTT DATA, Inc. if it is above the minimum.
Updated 2026-11-01, from our data and official sources.
Apply for this role at NTT DATA, Inc.
About the role
Responsibilities:
- Design and implement scalable ETL/ELT pipelines on Databricks for batch and streaming data.
- Architect and optimise Lakehouse solutions using Delta Lake and medallion patterns.
- Implement governance, access control and metadata management using Unity Catalog.
- Integrate data sources, orchestration (Databricks Workflows), and CI/CD for production delivery.
- Enable ML workflows with MLflow and support model training/inference pipelines.
- Apply performance tuning, partitioning and data modelling to reduce costs and improve query performance.
- Collaborate closely with solution architects, engineers, analysts and client stakeholders; provide mentoring and knowledge transfer.
Requirements:
- 5+ years data engineering experience; 3+ years hands-on with Databricks/Spark (PySpark/Scala).
- Strong SQL and Python skills; experience with dbt or equivalent transformation tooling.
- Practical knowledge of Delta Lake, Unity Catalog, MLflow and medallion architecture.
- Experience deploying on cloud platforms (AWS, Azure or GCP) and integrating cloud native services.
- Familiarity with orchestration, version control and CI/CD best practices.
- Strong consulting and communication skills; client-facing experience preferred.
Responsibilities
Design and implement scalable ETL/ELT data pipelines and Lakehouse architectures on Databricks, integrating batch and streaming sources. Optimize data models (Delta Lake, medallion architecture), enable governed data products, and collaborate with client stakeholders and cross-functional teams to deliver production-ready data solutions.
Requirements
Minimum 5–8 years in data engineering or data architecture with at least 3+ years on Databricks, a university degree, strong SQL and Python skills, and hands-on experience with cloud platforms (AWS/Azure/GCP). Familiarity with Databricks platform components (Unity Catalog, MLflow), ETL tools (DBT/Matillion/Talend), version control and CI/CD, and experience leading or mentoring engineers is required.
Key skills
- Databricks — in 37 other listings on The Stack
- Spark/PySpark — not in any other listing on The Stack
- Scala — in 28 other listings on The Stack
- Delta Lake — in 20 other listings on The Stack
- Unity Catalog — in 3 other listings on The Stack
- MLflow — in 24 other listings on The Stack
- DBT — in 99 other listings on The Stack
- SQL — in 512 other listings on The Stack
- Python
- AWS
- Azure
- GCP
On The Stack (as of 2026-11-01)
- This is NTT DATA, Inc.'s only listing on The Stack.
- 204 visa-sponsored jobs in the United Kingdom on The Stack, posted in the last 60 days.
- 39 visa-sponsored data engineer jobs in Europe on The Stack, posted in the last 60 days.
Frequently asked questions about NTT DATA, Inc.
Is this Databricks Data Engineer role still open?
It was posted on 2026-10-31 and is listed as active on The Stack. Confirm on NTT DATA, Inc.'s application page before applying.
Does NTT DATA, Inc. offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on NTT DATA, Inc.'s site.
Where is this role located?
The listing gives the location as London, GB, United Kingdom. It is marked on-site.
What skills does this role ask for?
The listing names: Databricks, Spark/PySpark, Scala, Delta Lake, Unity Catalog, MLflow, DBT, SQL, Python, AWS, Azure, GCP.