Full job description

We're seeking a Senior Data Engineer to play a key role in designing and delivering scalable, cloud-based data solutions that support business-critical decision-making. You'll work across the full data lifecycle, building robust pipelines, optimising performance, and helping drive best practice within a growing data function.

Client Details

Our client is a forward-thinking organisation undergoing significant investment in its data and technology capabilities. Operating in a fast-paced environment, they are leveraging modern cloud technologies to transform how data is used across the business and create a more data-driven culture.

Description

Design, develop, and maintain scalable data pipelines using Python and Databricks.
Build and optimise ETL/ELT workflows using Spark and Delta Lake.
Develop and maintain data models and lakehouse architectures.
Ensure high levels of data quality, reliability, governance, and security.
Optimise the performance of distributed data processing workloads.
Collaborate with analysts, engineers, and data scientists to support reporting and advanced analytics initiatives.
Implement monitoring, logging, and alerting frameworks across data platforms.
Support and mentor junior engineers while promoting engineering best practices.
£700-900 Day Rate (Inside IR35)
Contribute to the continual evolution of the organisation's data platform and architecture.

Profile

10+ years' experience in Data Engineering.
Strong commercial experience with Python.
Advanced hands-on knowledge of Databricks, including notebooks, workflows, jobs, and Delta Lake.
Strong experience with Apache Spark / PySpark.
Proven track record building and maintaining scalable ETL pipelines.
Strong SQL and data modelling expertise.
Experience working within AWS, Azure, or GCP environments.
Exposure to modern data warehousing platforms such as Snowflake, BigQuery, or Redshift.
Familiarity with orchestration tools including Airflow or Databricks Workflows.
Excellent communication skills with the ability to engage technical and non-technical stakeholders.
Strong problem-solving mindset and a passion for delivering high-quality data solutions.

Job Offer

Opportunity to influence the direction of a modern data platform.
Exposure to the latest cloud, data engineering, and lakehouse technologies.
Collaborative and highly skilled technical environment.
Clear opportunity to mentor others and shape engineering best practice.
Flexible working arrangements.

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Responsibilities

Full job description

Client Details

Description

Design, develop, and maintain scalable data pipelines using Python and Databricks.
Build and optimise ETL/ELT workflows using Spark and Delta Lake.
Develop and maintain data models and lakehouse architectures.
Ensure high levels of data quality, reliability, governance, and security.
Optimise the performance of distributed data processing workloads.
Collaborate with analysts, engineers, and data scientists to support reporting and advanced analytics initiatives.
Implement monitoring, logging, and alerting frameworks across data platforms.
Support and mentor junior engineers while promoting engineering best practices.
£700-900 Day Rate (Inside IR35)
Contribute to the continual evolution of the organisation's data platform and architecture.

Profile

10+ years' experience in Data Engineering.
Strong commercial experience with Python.
Advanced hands-on knowledge of Databricks, including notebooks, workflows, jobs, and Delta Lake.
Strong experience with Apache Spark / PySpark.
Proven track record building and maintaining scalable ETL pipelines.
Strong SQL and data modelling expertise.
Experience working within AWS, Azure, or GCP environments.
Exposure to modern data warehousing platforms such as Snowflake, BigQuery, or Redshift.
Familiarity with orchestration tools including Airflow or Databricks Workflows.
Excellent communication skills with the ability to engage technical and non-technical stakeholders.
Strong problem-solving mindset and a passion for delivering high-quality data solutions.

Job Offer

Opportunity to influence the direction of a modern data platform.
Exposure to the latest cloud, data engineering, and lakehouse technologies.
Collaborative and highly skilled technical environment.
Clear opportunity to mentor others and shape engineering best practice.
Flexible working arrangements.