Senior Data Engineer

Senior Data Engineer

6 Month contract with extension

Full-time

Inside IR35

Hybrid 1 day every two weeks in the office

Nottingham - NG1 4BX

Join our client in embarking on an ambitious data transformation journey using Databricks, guided by best practice data governance and architectural principles. To support this, we are recruiting for talented data engineers. As a major UK energy provider, our client is committed to 100% renewable energy and sustainability, focusing on delivering exceptional customer experiences.

It is initially a 6-month contract with potential to be extended. The role is Hybrid, with one day a week being based in their Nottingham office every two weeks, this is negotiable. It is a full-time role.

Accountabilities:

Develop and maintain scalable, efficient data pipelines within Databricks, continuously evolving them as requirements and technologies change.

Build and manage an enterprise data model within Databricks.

Integrate new data sources into the platform using batch and streaming processes, adhering to SLAs.

Create and maintain documentation for data pipelines and associated systems, following security and monitoring protocols.

Ensure data quality and reliability processes are effective, maintaining trust in the data.

Be comfortable with taking ownership of complex data engineering projects and develop appropriate solutions in accordance with business requirements.

Able to work closely with stakeholders and managing their requirements.

Actively coach and mentor others in the team and foster a culture of innovation and peer review within the team to ensure best practice.

Knowledge and Skills:

Extensive experience of Python preferred, including advanced concepts like decorators, protocols, functools, context managers, and comprehensions.

Strong understanding of SQL, database design, and data architecture.

Experience with Databricks and/or Spark.

Knowledgeable in data governance, data cataloguing, data quality principles, and related tools.

Skilled in data extraction, joining, and aggregation tasks, especially with big data and real-time data using Spark.

Capable of performing data cleansing operations to prepare data for analysis, including tran...