Senior Data Engineer (eDV)

Aker Systems designs, builds & operates advanced, ultra-secure data infrastructure, delivering data modernisation at enterprise scale to enable AI-driven transformation and seamless sharing of trusted data at scale, predominantly for highly regulated and Central Government clients in the UK. Aker has proven tech-enabled service offerings - covering the entire client lifecycle through strategic cloud & data capability leadership, secure cloud and data infrastructure modernisation, managed services in client environments and data & platform engineering. Aker powers AI digital transformation through trusted, enterprise scale data modernisation with proven mission critical, secure, trusted and real-time expertise & solutions. With deeply trusted relationships and influence, innovative technology and excellent delivery track record.

Client Focus

You will be working for national security and defence clients in the Southwest, across both short and long-lived programmes of work, as part of an Agile team of likeminded individuals that thrive on solving real-world problems, keeping the UK safe. Due to the nature of the work and the customers, you must hold enhanced DV Security Clearance.

Duties & Responsibilities

As a Data Engineer, you will help lead the development of a secure batch/real-time data-centric platforms and services for National Security and Defence clients leveraging the latest commercial and open-source technologies in private and public cloud environments.

This involves getting data from a variety of different sources, getting it into the right format, assuring alignment to target models, and ensures that users can get the data quickly for analysis.

The Data Engineer requires substantial expertise in a broad range of software development and programming fields (JAVA, Python, C++ and many others).

These professionals have knowledge of data analysis, end user requirements analysis, and business requirements analysis to develop a clear understanding of the business needs and to incorporate these needs into technical solutions. They have a solid understanding of physical database design principles, and the system development life cycle. These individuals must work well in a team environment.

• Works on multiple projects as a technical team member or lead driving user story analysis and elaboration, design and development of software applications, testing, and builds automation tools.
• Translates complex functional and technical requirements into detailed architecture, design, and high performing software
• Codes, tests, and documents new or modified data pipelines that meet functional / non- functional business requirements.
• Expands and grows data platform capabilities to solve new data and analytics problems.
• Conducts data analysis, identifying feasible solutions and enhancements to data processing challenges.
• Ensures that data models are consistent with the data architecture (e.g. entity names, relationships, and definitions).
• Performs root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

Core Competencies

The successful candidate will have at least 5 years professional experience delivering production grade cloud solutions.

• Data pipeline development using data processing technologies and frameworks.
• Implement data models and solutions that meets the intended solution/requirements.  
• Agile or other rapid application development methods.
• Strong SQL development skill level, sufficient to implement data models successfully.
• Data modelling and understanding of different data structures and their benefits and limitations under particular use cases
• Experience in AWS including practical experience with core services such as EC2, RDS, Lambda, Athena & Glue.
• Programming or scripting languages, such as Java, Python.
• Experience working in DevSecOps environments and Zero Trust Architecture
• Commercial Experience in deploying data applications on AWS and other public and private cloud (hybrid) environments
• Developing and operating using open source and commercial software within a cloud-centric environment
• Lead the development of CI/CD pipelines for data engineering tasks
• Test Driven Development with appropriate tools and frameworks
• Distributed event streaming technologies, such as Kafka, Flink and Spark