Senior Engineering Manager - HVDC Control & Protection

Hunter Philips Executive Search
Birmingham
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineering Manager

Analytics Engineering Manager

Machine Learning Manager

Machine Learning Engineering Manager

Senior Data Engineer

Senior Security Architect

Job Profile Summary:As a Control & Protection Application Senior Engineering Manager, you will be leading Engineering teams and working across two engineering disciplines. Solution and engineering centre in all aspects of HVDC Control & Protection system, supports the design and implementation of HVDC Control & Protection Systems by analysing customer requirements, assessing the necessary deviation from standard solutions, and provide technical solution that meets the project delivery and Tender objectives.


This includes the following.

  • Recruit and Developing Department talent
  • Engineering process management
  • Provide technical guidance.
  • Drive consistent design practices and common global processes for projects.
  • Interface with customers


Essential Responsibilities

  • Senior Control & Protection Engineering Manager oversees a team of engineers responsible for designing, developing, implementing, and maintaining complex control systems within an organization, leading the technical direction of projects, ensuring systems meet performance standards, and collaborating with other departments to integrate control systems across various operations, often requiring strong leadership, technical expertise in control system design, and knowledge of industry regulations and safety standards.


Team Leadership:

  • Manage a team of control & Protection system engineers, assigning tasks, providing technical guidance, and overseeing project execution.
  • Recruit, develop, and mentor control system engineers to maintain a high-performing team.
  • Foster collaboration and communication within the team and with other departments.


Technical Strategy:

  • Define the overall technical vision for control system design and architecture across the organization.
  • Stay abreast of emerging control system technologies and identify opportunities for innovation and improvement.
  • Development of PSCAD Network Model, Control MATLAB application Model, Control system block diagram, ONM Manuals. MATLAB application unit and system integration testing.
  • PSSE/PSCAD and PSSE/RSCAD Power system network conversion, modelling and verification
  • HVDC System in electromagnetic transient tools like PSCAD, EMTP-RV etc.
  • Plant modelling in various simulation tools (MATLAB, RSCAD, PSCAD etc) and its verification


Project Management:

  • Lead the planning and execution of control system projects from concept to deployment, including budget and timeline management.
  • Ensure that project plans contain the necessary activities and studies required to meet the requirements of the customer and the proposed technical solution.
  • Manage the engineering resources, workload, schedule and project milestones.
  • Define the project work breakdown structure (WBS), resources and skill levels required to meet the delivery timescales.
  • Ensure projects comply with relevant safety, quality, and regulatory standards.
  • Define the project work breakdown structure (WBS), resources and skill levels required to meet the delivery timescales.


Qualifications / Essential Requirements

  • Engineering degree or equivalent including power systems and power electronics subjects or proven equivalent knowledge and experience in HVDC business.
  • More than 10 years’ experience in HVDC industry and 3+ years’ experience in senior leadership position
  • Strong sense of urgency and ability to identify and manage team organisational risks
  • Proven skills in managing and leading team with strong technical background
  • Strong oral and written communication skills. Strong interpersonal and leadership skills. Demonstrated ability to analyse and resolve problems. Demonstrated ability to lead programs skills.

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 Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

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

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.