DataBricks Specialist

Ciandt; Greater London; On-site; GBP 70,000 - GBP 90,000; Full time

Job summary

A leading technology company in Greater London is seeking a Senior Data Engineer who will lead the design and development of robust data pipelines. The role includes integrating and transforming data from diverse sources and collaborating closely with analytics teams. Candidates should have proven experience in building large-scale data pipelines, strong programming skills in Python and SQL, and an understanding of modern DataOps practices. Join us in driving innovation and transformation in data management.

Qualifications

• Proven experience in building and managing large-scale data pipelines in Databricks.
• Deep understanding of ETL/ELT frameworks and data warehousing.
• Hands-on experience with version control (Git) and CI/CD pipelines.

Responsibilities

• Develop and maintain data pipelines.
• Integrate data from various sources such as APIs and databases.
• Collaborate with teams to understand data requirements.

Skills

Building and managing large-scale data pipelines

Programming skills in Python

Programming skills in SQL

Deep understanding of ETL/ELT frameworks

Hands-on experience with modern DataOps practices

Familiarity with cloud platforms (AWS, Azure, GCP)

Strong problem-solving skills

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.