At a Glance
- Tasks: Develop and enhance cloud-based data platforms while tackling modern analytics challenges.
- Company: Join a growing data-driven organisation undergoing exciting digital transformation.
- Benefits: Competitive salary up to £65,000, hybrid work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and high-quality data solutions.
- Why this job: Shape the future of data solutions and influence technology decisions across the business.
- Qualifications: Experience with Azure technologies, strong SQL skills, and Python scripting capabilities.
The predicted salary is between 63000 - 77000 £ per year.
This is an excellent opportunity for a Senior Analytics Engineer to play a key role in a growing data-driven organisation undergoing significant digital transformation. You will help shape the future of a cloud-based data platform, working on modern analytics engineering challenges while influencing technology decisions across the business.
ROLES AND RESPONSIBILITIES:
- Develop, maintain, and enhance cloud-based data platforms and analytics solutions
- Design and build scalable ETL and ELT pipelines to support reporting and data products
- Work closely with stakeholders to translate business requirements into technical solutions
- Develop and optimise data warehouses, data marts, and reporting environments
- Ensure high standards of data quality, performance, reliability, and governance
- Automate data processes and deployments using modern engineering practices
- Monitor, troubleshoot, and continuously improve data infrastructure
- Contribute to data architecture decisions and support the modernisation of legacy systems
- Create clear technical documentation and maintain best practices across data engineering workflows
- Collaborate with developers, analysts, and business teams to deliver impactful data solutions
YOUR SKILLS AND EXPERIENCE:
- Strong commercial experience with Azure-based data technologies such as Azure SQL, Azure Data Factory, Microsoft Fabric, Synapse, or related platforms
- Expertise in designing and maintaining modern data warehouse architectures
- Advanced SQL skills and experience with CI/CD processes and Azure DevOps
- Strong Python scripting capabilities for automation, orchestration, and pipeline optimisation
- Experience working with ETL and ELT frameworks and data management best practices
- Knowledge of data security, governance, and regulatory requirements
- Experience with analytics and visualisation tools such as Power BI or similar platforms
- Familiarity with Git version control and collaborative development practices
- The ability to communicate effectively with both technical and non-technical stakeholders
- A proactive approach to problem-solving and delivering high-quality solutions
APPLY BELOW!
Senior Analytics Engineer in Banbury employer: Harnham
Join a leading UK-based media organisation at the forefront of digital transformation, where your role as Director of Streaming Product and Growth will be pivotal in shaping the future of their subscription services. With a strong emphasis on innovation and a collaborative work culture, you'll have access to significant growth opportunities, competitive salary packages, and a performance-based bonus structure, all while working in a dynamic environment that values data-driven decision making and customer-centric strategies.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer in Banbury
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We think you need these skills to ace Senior Analytics Engineer in Banbury
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!
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✨Brush Up on Your Statistics
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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
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✨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.
