DataBricks Specialist

Ciandt; Greater London; On-site; GBP 68,000 - GBP 85,000; Full time

Job summary

A leading technology firm in the Greater London area is seeking a Senior Data Engineer to lead the design and development of data pipelines. You will work closely with business and analytics teams to ensure high-quality data deliverables. The ideal candidate should have proven experience in building large-scale data pipelines, strong programming skills in Python and SQL, and familiarity with cloud platforms such as AWS or Azure. This role emphasizes collaboration, innovation, and transformation in data engineering.

Qualifications

• Proven experience in building and managing large-scale data pipelines in Databricks.
• Strong programming skills in Python and SQL for data processing.
• Hands-on experience with version control and CI/CD pipelines.

Responsibilities

• Develop and maintain data pipelines.
• Integrate data from various sources.
• Collaborate with analytics teams to understand data requirements.

Skills

Data pipeline development

Python programming

SQL processing

ETL/ELT frameworks

DataOps practices

Troubleshooting skills

Tools

Databricks

AWS

Azure

GCP

Job description

As a Senior Data Engineer, you will lead the design and development of robust data pipelines, integrating and transforming data from diverse data sources such as APIs, relational databases, and files. Collaborating closely with business and analytics teams, you will ensure high-quality deliverables that meet the strategic needs of our organization. Your expertise will be pivotal in maintaining the quality, reliability, security and governance of the ingested data, therefore driving our mission of Collaboration, Innovation, & Transformation.

Key Responsibilities:

• Develop and maintain data pipelines.
• Integrate data from various sources (APIs, relational databases, files, etc.).
• Collaborate with business and analytics teams to understand data requirements.
• Ensure quality, reliability, security and governance of the ingested data.
• Follow modern DataOps practices such as Code Versioning, Data Tests and CI/CD.
• Document processes and best practices in data engineering.

Required Skills and Qualifications:

Must-have Skills:

• Proven experience in building and managing large-scale data pipelines in Databricks (PySpark, Delta Lake, SQL).
• Strong programming skills in Python and SQL for data processing and transformation.
• Deep understanding of ETL/ELT frameworks, data warehousing, and distributed data processing.
• Hands-on experience with modern DataOps practices: version control (Git), CI/CD pipelines, automated testing, infrastructure-as-code.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and related data services.
• Strong problem-solving skills with the ability to troubleshoot performance, scalability, and reliability issues.