• 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.

This is a site‑based role, employees work 3+ days (60%+) per week from a Viasat office or work location within a standard five‑day workweek.

• 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.

• 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.

• 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.

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