At a Glance
- Tasks: Design and maintain data and ML infrastructure to support innovative projects.
- Company: Join TEKEVER, a leader in unmanned technology and innovation.
- Benefits: Competitive salary, flexible working, health insurance, and career development opportunities.
- Other info: Dynamic team environment with clear career growth and skill development.
- Why this job: Shape the future of technology while making a real impact on global safety.
- Qualifications: Experience in data engineering, MLOps, and strong programming skills required.
The predicted salary is between 63000 - 77000 £ per year.
Are you ready to revolutionise the world with TEKEVER?
At TEKEVER, we lead innovation in Europe as the European leader in unmanned technology, where cutting-edge advancements meet unparalleled innovation.
Digital | Defence | Security | Space
We operate across four strategic areas, combining artificial intelligence, systems engineering, data science, and aerospace technology to tackle global challenges - from protecting people and critical infrastructure to exploring space.
We offer a unique surveillance-as-a-service solution that delivers real-time intelligence, enhancing maritime safety and saving lives.
Our products and services support strategic and operational decisions in the most demanding environments - whether at sea, on land, in space, or in cyberspace.
Become part of a dynamic, multidisciplinary, and mission-driven team that is transforming maritime surveillance and redefining global safety standards.
At TEKEVER, our mission is to provide limitless support through mission-oriented game-changers, delivering the right information at the right time to empower critical decision-making.
If you're passionate about technology and eager to shape the future - TEKEVER is the place for you.
Mission
As a Data & ML Platform Engineer, you will play a critical role in designing, building and maintaining the infrastructure that power our data processing pipelines and machine learning workflows that support our data-driven initiatives, as well as supporting the evolution of our Data & AI Platform.
You will work at the intersection of data engineering, MLOps, and platform development and ensure that our data & AI infrastructure is robust, scalable and efficient.
The ideal candidate will have a strong background in platform engineering, with experience in data science, machine learning and or data engineering.
What will be your responsibilities
- Data and ML infrastructure: Design and implement scalable data and ML infrastructure using modern cloud and on-prem distributed technologies and frameworks.
- Data Pipeline Development: Design, develop and maintain scalable and efficient data pipelines to collect, process and store large volumes of data from various sources.
- Database Management: Manage and optimize databases and data warehouses to ensure data integrity, performance and availability.
- Data Integration: Integrate data from multiple sources, including APIs, databases and external data providers, to create unified datasets for analysis.
- Self-Service Tools: Develop self-service tools that enable stakeholders to extract insights from Data and Machine Learning models.
- Data & AI Platform development & expansion: support the expansion of our Data & AI Platform.
- Security & Compliance: Ensure data security, privacy, and compliance.
- Data Quality Assurance: Implement data validation and quality assurance processes to ensure the accuracy and consistency of data.
- Collaboration: Work closely with data scientists, analysts and other stakeholders to understand platform requirements and provide the necessary data infrastructure and support.
- Monitoring & Performance
Optimization: Implement monitoring, observability, and alerting for data and ML systems and optimize for performance, reliability, and cost-effectiveness.
- Documentation: Maintain comprehensive documentation of platform components, APIs, and workflows to ensure knowledge sharing and user adoption (e. g. data pipelines, database schemas, Machine Learning systems, etc.)
Profile and requirements
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
- Preferred location of working: UK, Portugal , France and/or Spain
- Experience: 3+ years of experience in data & ML platform engineering or a similar role.
- Analytical Skills: Strong analytical and problem-solving skills with a focus on delivering scalable and efficient data solutions.
- Communication: Excellent verbal and written communication skills, with the ability to effectively collaborate with technical and non-technical stakeholders.
- Language Requirements: Advanced proficiency in Portuguese and English, with proven fluency at the C2 level in both languages.
- Attention to Detail: High attention to detail and a commitment to ensuring data quality and accuracy.
- Adaptability: Ability to work in a fast-paced, dynamic environment and manage multiple priorities simultaneously.
Technical Skills
- Proficiency in programming languages such as Python, Go, Java, or Rust.
- Strong knowledge of containerization technologies (e. g. Docker) and orchestration systems (e. g. Kubernetes) in production environments.
- Experience with SQL, database management systems (e. g., My SQL, Postgre SQL, SQL Server), data modeling and schema design.
- Experience with cloud platforms (e. g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud.
- Familiarity with big data technologies (e. g. Spark), data warehousing solutions, data pipeline orchestration (e. g. Airflow), and database systems (SQL and no SQL).
- Design and manage MLOps pipelines to support model training, deployment and monitoring at scale.
- Experience implementing observability stacks and logging pipelines (e. g., Prometheus, Grafana, Loki, ELK).
- Experience with Ia C frameworks (e. g. Ansible, Terraform),
- Understanding of Dev Ops best practices and tools: GIT, CI/CD, telemetry and monitoring, etc.
What we have to offer you
- At TEKEVER, we offer a comprehensive package designed to reward, support, and develop our people.
This includes a highly competitive salary with a discretionary annual bonus and a company pension contribution match of up to 10%.
To support your wellbeing, we provide 25 days annual leave plus Bank Holidays, Private Medical Insurance (with optional family cover), Private Dental care, and an Employee Assistance Programme.
We are deeply committed to investing in future talent; our scale allows us to provide clear career development opportunities and dedicated initiatives to boost your skill sets, ensuring you remain future-ready for the evolving workplace.
Furthermore, our team enjoys a flexible hybrid working model, typically three days a week at our core UK sites like Bristol, and access to a bespoke rewards platform featuring a variety of high street discounts and salary sacrifice schemes, including Electric Car, Cycle to Work, and Technology options.
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Data & ML Platform Engineer employer: Mobizy
Tekever UK is an exceptional employer, offering a dynamic work environment where innovation meets operational excellence. As a Supply Chain Manager in Swindon, you will benefit from a supportive culture that prioritises employee growth through continuous improvement initiatives and collaborative teamwork. With competitive salary packages, generous holiday allowances, and comprehensive health benefits, Tekever is committed to fostering a diverse and inclusive workforce while empowering you to make a meaningful impact in the procurement landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Data & ML Platform Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Mobizy!
✨Show Off Your Projects
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✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Mobizy.
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We think you need these skills to ace Data & ML Platform Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Mobizy, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Mobizy. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Mobizy
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Mobizy!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
