Principal Security Data Analyst

Oracle
Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Principal Software Engineer

UNPAID VOLUNTEER - Principal/Senior Technology Officer (Artificial Intelligence)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Principal Naval Architect (Weights)

Oracle’s Software Assurance organization has the mission is to make application security and software assurance, at scale, a reality. We are a diverse and inclusive team of architects, researchers, and engineers, combining our unique perspectives and expertise to create secure and innovative solutions to complex challenges. With the resources of a large enterprise and the agility of a start-up, we are working on a greenfield software assurance project.


Work You’ll Do

We are seeking a Security Data Analyst to join our team. This role will combine data analysis, security research, and development skills where you will be responsible for designing, developing a platform capable of analyzing large datasets for security and compliance requirements. You will leverage your expertise in cybersecurity to proactively identify and address emerging threats, ensuring that secure coding practices are seamlessly integrated into every stage of development.


What You’ll Bring

  • Bachelor’s degree in computer science, Engineering, or a related field (or equivalent work experience).
  • 5+ years of experience in software/platform development/engineering from front end (web), mobile, back end, ad tech, or analytics dataflows backgrounds.
  • Extensive experience in dataflows, or similar roles in data management with proven experience building automated and scalable platforms for data-intensive applications.
  • Experience with navigating and handling large data sets and the ability to design and implement scalable and maintainable systems
  • Strong background in API development and associated architectural patterns such as REST or gRPC
  • Programming experience in Python, Go, Java, or similar.
  • Experience with data science concepts such as data preparation, exploration, modelling and the ability to apply this process when handling structured or unstructured data
  • Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy
  • API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc.
  • Strong knowledge of database management systems (DBMS) such as MySQL
  • Hands-on experience with security and compliance frameworks and standards.
  • Knowledge of performance optimization techniques for mobile applications, including memory, CPU and network efficiency.
  • Excellent problem-solving and analytical skills.
  • Strong collaboration and communication skills, with the ability to work in cross functional teams and explain complex technical concepts to non-technical stakeholders.


Nice to Have:

  • Experience with OCI cloud-based services
  • Experience with machine learning or AI in security applications.
  • Experience in Agile methodologies and using project management tools like JIRA and confluence.
  • Knowledge of Software Assurance programs

Career Level - IC5


Responsibilities:

  • Architect and develop a secure, high-performance platform to ingest, parse, and analyze large volumes of API data stored in a MySQL database.
  • Work closely with internal and client teams to analyze, define and implement data rules and data flows, translating these into an auditable tool.
  • Scope and execute threat analysis to research, evaluate, track, and manage information security threats and vulnerabilities in data flows.
  • Ensure the tooling is secure by collaborating with architects and security teams to implement best practices for compliance, data privacy, and protection, while integrating tools and frameworks to assess APIs against OWASP and other relevant security standards (NIST, ISO-27001, PCI-DSS, HIPAA, FedRAMP)
  • Automate security and compliance controls into the platform for continuous monitoring and reporting.
  • Execute MySQL queries to ensure data integrity and consistency
  • Create intuitive dashboards and reports for stakeholders.
  • Create tools to help engineering teams identify security-related weaknesses
  • Stay up to date with the latest trends and technologies, contributing to ongoing improvements of platform architecture and best practices.
  • Maintain clear, comprehensive documentation on the platform architecture, services, and technical decisions to support internal teams and future development.
  • Mentor junior engineers and provide technical guidance.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.