Job Description

Junior Software Engineer & Quality Assurance Analyst in London
London
Full–time
PCD310100

Job description
The organisation is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400, 000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide.

Responsibilities:
• Software Development Support:
• Assist senior engineers in writing, testing, and debugging clean, scalable code for data-related applications, primarily using general-purpose programming languages.
• Gain exposure to the full software development lifecycle and contribute to code reviews under mentorship.
• Quality Assurance (QA) and Testing:
• Execute basic unit, integration, and end-to-end tests for data pipelines and software components to ensure reliability.
• Learn to design and execute manual and automated tests for internal and external APIs.
• Accurately document test results, log defects, and verify fixes in collaboration with the development team.
• Data Pipeline Assistance:
• Support the team in monitoring and maintaining core data pipelines for acquiring, ingesting, and integrating diverse datasets.
• Assist with automating basic data pipeline tasks to improve efficiency.
• Data Preparation and Exploration:
• Support data scientists with fundamental data cleaning, transformation, and preparation tasks for model development.
• Perform basic data querying and manipulation using database-query languages.
• Cloud and API Learning:
• Learn about and assist with basic setup and consumption of cloud services (e.g., a major public-cloud platform, including machine-learning platform services) for data and model deployment.
• Gain experience with leveraging APIs for data access and integration.
• Web Scraping & Data Acquisition:
• Learn and assist with basic web scraping tasks to gather relevant public data from online sources under guidance.
• Emerging Technology Exposure:
• Develop a foundational understanding of MLOps practices and data-related techniques used in our AI projects.
• Collaboration:
• Actively participate in cross-functional team discussions, including data scientists, software engineers, and business analysts, to understand requirements and contribute to solutions.