Role Overview – Ficher Analytics is hiring a Data Engineer for a full-time, remote position serving UK-based operations. This position is ideal for skilled technical professionals with strong data engineering expertise, proficiency with data technologies, and the ability to design data pipelines effectively, manage data infrastructure, develop ETL solutions, ensure data quality, support analytics capabilities, and maintain data excellence within a dynamic data analytics business environment.

Data Pipeline Development and Management – You will design and develop data pipelines by creating extraction processes, building transformation logic, and implementing loading mechanisms. You will architect scalable pipelines, optimize pipeline performance, and maintain pipeline stability. You will document pipeline processes and support continuous pipeline improvement.

ETL Process Development – You will develop Extract-Transform-Load (ETL) processes by designing workflows, implementing data transformations, and automating data movement. You will build efficient ETL solutions, monitor ETL performance, and troubleshoot ETL issues. You will optimize ETL performance and ensure data accuracy throughout processes.

Data Warehouse Design and Development – You will design and develop data warehouse solutions by creating data models, designing schema structures, and building warehouse infrastructure. You will optimize warehouse performance, support scalability, and maintain data organization. You will document warehouse architecture and support warehouse optimization.

How to Apply:

Send your updated CV to info@ficheranalytics.uk. Please highlight your data engineering experience, specific examples of data pipeline and ETL projects you have developed, your expertise with cloud platforms and big data technologies, proficiency with Python, SQL.

About the Company:

Ficher Analytics is a dynamic data analytics organization serving UK and international clients with a strong commitment to data infrastructure excellence, data engineering quality, and analytics innovation.