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# Big Data Engineer

- **Company:** IBM
- **Location:** UK
- **Salary:** £43,664.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Unit Testing, Big Data, Unix, Code Review, Continuous Integration, Information Engineering, Data Infrastructure, Data Security, Relational Databases, Software Design Patterns, Apache Hadoop, Apache Hive, MariaDB, MySQL, Pair Programming, Performance Tuning, Scrum Methodology, Shell Script, Apache Yarn, Apache Spark, Extreme Programming
- **Published:** October 25, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5210484883

## About the Role

* Solid hands-on experience with HADOOP, SPARK and HIVE using Java. Expert level knowledge in Spark Tuning and ensuring best practices across project.
 * Experience in Big Data Architecture, tools and technologies. Experience leading teams and interfacing with stakeholders across project in technical and functional areas. Experience interfacing with end users.
 * A detailed understanding and experience of development best practices in below areas: Continuous Integration, branching and merging, pair programming, code reviews, unit testing, agile methodologies (Scrum/XP),
 * Design Patterns UNIX/ Shell scripting. RDBMS, preferably MariaDB, MySQL. CI/CD concepts. YARN Scheduling Tools and techniques Core JAVA Scala Hand

Preferred Technical And Professional Expertise

 * Proven interpersonal skills while contributing to team effort by accomplishing related results as needed
 * Up-to-date technical knowledge by attending educational workshops, reviewing publications

## Description

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs.

Your Primary Responsibilities Include

Design, build, optimize and support new and existing data models and EL processes based on our clients Business requirements.

 * Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization.
 * Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too.