At a Glance
- Tasks: Design and build solutions to manage and utilise data for actionable insights.
- Company: Join Viasat, a leader in global connectivity and innovation.
- Benefits: Competitive pay, relocation assistance, and comprehensive health benefits.
- Other info: Site-based role with opportunities for career growth and collaboration.
- Why this job: Make an impact with cutting-edge technology in a dynamic team environment.
- Qualifications: Bachelor's degree in relevant fields and foundational skills in Python and SQL.
The predicted salary is between 63000 - 77000 £ per year.
About us
One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team.
What you'll do
The Mobility Data Products team sits within the Data & Artificial Intelligence function which is responsible for the platforms, infrastructure, and governance required to transform Viasat's network data into actionable insights and automated AI solutions. By providing integrated data streaming, advanced analytics, and responsible AI frameworks, the function enables data-driven decision-making and optimizes operations across the enterprise. The Mobility Data Products team builds the monitoring and reporting tools and services for our In-Flight Connectivity (IFC) products. These rich tools enable our users to visualise the vast array of data traversing our satellite networks, providing insights into the quality of service being delivered, as well as how our satellite connectivity services are being utilised by our end customers. The performance of these tools and the accuracy of the information they provide is of critical importance to not only Service Delivery, Marketing, and Strategic teams across the business, but also by our customers, suppliers and partners.
As a Data Engineer within the Mobility Data Products team, you will be responsible for designing and building the deployment and operation of solutions to capture, manage, store and utilize structured and unstructured data from internal and external sources. All with a strong focus on AI-driven development towards stability, modernization, and continuous improvement.
The day-to-day
- Establishing and building processes based on business and technical requirements to channel data from multiple inputs and store using any combination of distributed (cloud) structures, local databases or other applicable storage forms.
- Develop and own technical tools leveraging big data to cleanse, organise and transform data to maintain data structures and integrity on an automated basis in real time.
- Develop solutions that are functional, reliable, maintainable, scalable and extensible.
- Resolving complex issues and bugs that may impact multiple business areas.
- Maintaining relationships with internal and external stakeholders.
- Collaborating with Data Engineers, Software Engineers, and Data Scientists both within the team and across the business.
- Participating in on-call rotations to provide technical support outside regular business hours, ensuring system reliability and timely incident response.
- Excellent verbal and written communication abilities. You will be required to communicate both verbally and in written form with remote international teams very frequently.
- Writing clear and relevant documentation.
Additional Information
This position is site-based. Site-based employees work 3+ days (60%+) per week from a Viasat office or work location within a standard five-day work week. Relocation assistance is available pending eligibility.
What you'll need
- Education: Completion of Bachelor's degree or higher in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, Mathematics, Physics or a related field.
- Citizenship: This position requires a Valid Work Permit or Visa for the country you would be located and working from.
- Additional: Foundational level Python, including data manipulation packages; Foundational level SQL; Foundational level AI assisted coding and automation tools (Claude Code preferred); Familiarity with Cloud-based data platforms (GCP preferred); Familiarity with Software Development Lifecycle, including source control (Git preferred) and CI/CD practices (automation and testing).
What will help you on the job
- Experience with Cloud platforms, and AI assisted coding.
- Familiarity with big data and data processing technologies.
- Creative problem-solving.
- Meticulous attention to detail.
- Comfortable with working independently and taking ownership.
- Willingness to work outside of area of expertise.
At Viasat, we consider many factors when it comes to compensation, including the scope of the position as well as your background and experience. Base pay may vary depending on job-related knowledge, skills, and experience. Additional cash or stock incentives may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered.
EEO Statement
Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic.
Data Engineer, Early Career employer: Viasat
Viasat is an excellent employer that fosters a dynamic work culture, encouraging collaboration and innovation among its employees. With a strong focus on professional development, the company offers numerous growth opportunities within the corporate real estate sector, particularly in the vibrant EMEA and APAC regions. Employees benefit from a supportive environment that values their contributions and promotes a healthy work-life balance, making it a rewarding place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, Early Career
✨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 Viasat!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer, Early Career at Viasat.
✨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 Viasat.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer, Early Career at Viasat, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer, Early Career
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 Viasat, 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 Viasat. 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 Viasat
✨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 Viasat!
✨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.