At a Glance
- Tasks: Transform raw data into clean datasets and develop scalable data solutions.
- Company: Join Viasat, a global leader in innovative communication technology.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment focused on continuous improvement and knowledge sharing.
- Why this job: Make a real impact by solving global challenges with data-driven insights.
- Qualifications: Advanced SQL skills and experience with data modelling and orchestration tools.
The predicted salary is between 36000 - 60000 £ 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
- Develop high quality data models that transform raw data into clean, analytics-ready datasets using tools like SQL, Python, dbt, BigQuery and Prefect.
- Work closely with the Data Product Owner and our product stakeholders to understand data requirements and translate business and analytical needs into scalable ‘product marts’.
- Implement and maintain data quality checks, documentation and version control to ensure reliability and transparency in analytics workflows.
- Support Agile delivery practices by participating in refinement and prioritisation exercises and taking ownership of your own work backlog to ensure timely delivery of analytical products.
The day-to-day
- Write performant SQL queries to build and enhance datasets used for business dashboard, reporting and analysis.
- Design and lead the development of flexible, scalable data solutions that meet immediate business needs, support AI integration and adapt to evolving future developments.
- Investigate and resolve data issues by debugging pipelines, validating data outputs and collaborating with source system teams.
- Document key logic, assumptions and dependencies within your data models to ensure they are understandable and maintainable.
- Work across teams to prioritise work based on business impact and support end users in accessing and understanding the data.
- Seek opportunities to reduce manual effort and improve consistency across datasets.
What you’ll need
- Advanced SQL skills with experience working in modern data warehouses particularly GCP BigQuery.
- Familiarity with the Software Development lifecycle, data quality frameworks, system observability, and experience with source control tools like GitHub.
- Hands on experience with dbt or similar transformation tools.
- Strong data modelling principles, including star schema, and best practices for building scalable data assets that can be used in BI and other user facing tools.
- Experience working with data pipeline orchestration tools like Prefect or Airflow and comfortable working with Python for data orchestration.
- Ability to communicate clearly with both technical and non-technical stakeholders, translating data into business value.
- Comfort working in Agile environments with focus on iterative development, feedback and continuous improvement.
What will help you on the job
- Has a curious and problem-solving approach, comfortable taking ownership and accountability, and with a desire to understand how data supports our products and commercial goals.
- Has passion for building clean, efficient and well documented data solutions.
- Is willing to share knowledge and support colleagues, especially in tools like dbt, SQL and best practices for data model development.
- Has a growth mindset, embracing change and supporting colleagues as we continue to grow as a team.
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.
Senior Analytics Engineer 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 Senior Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Viasat on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Senior Analytics Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for those interviews by brushing up on your SQL and Python skills. Practice writing queries and building data models that could impress the hiring team. Show them you can turn raw data into something meaningful!
✨Tip Number 3
Don’t forget to showcase your problem-solving skills! Be ready to discuss how you've tackled data issues in the past, especially in Agile environments. They want to see your thought process and how you approach challenges.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Viasat team. Let’s get you that dream job!
We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with SQL, Python, and data modelling. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Problem-Solving Skills:In your application, share examples of how you've tackled data issues or improved processes in previous roles. We love candidates who can demonstrate a curious and problem-solving mindset, so let us know how you’ve made an impact!
Communicate Clearly:Remember, we’re looking for someone who can bridge the gap between technical and non-technical stakeholders. Use your application to show off your ability to translate complex data concepts into business value – clarity is key!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Viasat
✨Know Your Tools Inside Out
Make sure you’re well-versed in SQL, Python, dbt, and BigQuery. Brush up on your skills and be ready to discuss specific projects where you've used these tools. Being able to share real examples will show that you can translate technical knowledge into practical solutions.
✨Understand the Business Impact
Before the interview, research Viasat’s mission and how data plays a role in their operations. Be prepared to discuss how your work as an Analytics Engineer can drive business value and support their goals. This shows you’re not just a techie but someone who understands the bigger picture.
✨Prepare for Agile Discussions
Since the role involves Agile practices, think of examples from your past experiences where you’ve worked in Agile environments. Be ready to talk about how you prioritised tasks, collaborated with teams, and adapted to changes. This will demonstrate your comfort with iterative development.
✨Show Your Problem-Solving Skills
Viasat is looking for someone with a curious mindset. Prepare to discuss challenges you’ve faced in data modelling or pipeline orchestration and how you resolved them. Highlighting your problem-solving approach will resonate well with their desire for accountability and ownership.