At a Glance
- Tasks: Contribute to data pipelines, AI features, and dashboards while learning from experienced engineers.
- Company: Ciphr, a people-first tech company focused on data and AI solutions.
- Benefits: Private medical, 30 days holiday, flexible work, and personal growth opportunities.
- Why this job: Join a dynamic team shaping the future of HR technology with innovative data solutions.
- Qualifications: Experience in data engineering, proficiency in Python and SQL, and a passion for learning.
- Other info: Hybrid work model with a focus on collaboration and personal development.
The predicted salary is between 28800 - 43200 £ per year.
Be a key contributor to Ciphr’s data & AI platform. We’re growing our Data Science & Analytics team and looking for a Junior Analytics Engineer to help deliver the data and AI products behind our HR technology—pipelines, transformations, dashboards and AI‑powered features. You’ll learn from senior engineers, build core skills across the modern data stack, and take ownership of increasingly impactful work.
What you’ll own and deliver:
- Contribute to and take ownership of key elements of our data platform, including data pipelines, transformations, and semantic models using tools such as Snowflake, dbt, and Fabric.
- Support the delivery of AI-driven features, assisting in testing, monitoring, and maintaining solutions built using large language models (LLMs), Model Context Protocol (MCP), and other AI frameworks.
- Build and maintain dashboards and visualisations that turn data into meaningful insights for internal and customer stakeholders.
- Assist in the implementation of DevOps and CI/CD practices, working with Terraform, Git, and Azure DevOps to deploy data and AI assets.
- Lead on data quality and documentation processes, ensuring the accuracy, traceability, and compliance of all data outputs.
- Embed security and data protection principles into all development and data handling activities, ensuring solutions meet Ciphr’s compliance and governance standards.
- Collaborate across the data team and wider business to understand data needs and contribute to ongoing projects.
- Identify and help implement opportunities to improve efficiency, quality, and reliability across data pipelines, automation, and analytics workflows.
- Continuously learn and experiment with new tools and techniques, from Python and SQL development to automation and AI integration.
What good looks like here:
- Growth in technical skills and the ability to deliver reliable, production-ready outputs is demonstrated with increasing independence.
- High quality and accuracy in data and reporting solutions are evidenced by stakeholder trust and reduced rework.
- Solutions are designed to be secure, efficient, and easily adopted by end users and internal teams.
- Contributions to code reviews, learning sessions, and collaborative projects are recognised.
- Positive feedback is received from senior engineers and product stakeholders regarding contributions and responsiveness.
- Documentation is kept clear and governance and DevOps standards are adhered to.
- Curiosity, initiative, and continuous learning are made visible and aligned to team objectives.
- Opportunities to streamline workflows and improve delivery speed and quality are proactively identified and acted upon.
What you’ll bring:
- Hands-on experience in data engineering, analytics, or computer science.
- Proficiency in Python and SQL, with a keen interest in building your skills.
- Experience with cloud data platforms (Snowflake, Azure, or similar) and willingness to learn modern data stack tools (dbt, Fabric).
- Good understanding of data visualisation principles.
- Strong attention to detail, communication skills and teamwork.
- Curiosity, adaptability, and a genuine passion for learning new technologies.
- Exposure to tools such as Power BI, Terraform and Azure DevOps.
- Interest in AI/ML concepts and practical applications (e.g., large language models, GitHub Copilot).
- Aware of data governance and compliance principles.
How we work:
Hybrid, UK‑based: outcome‑focused with regular in‑person anchor days for collaboration (typically monthly), and flexible presence aligned to role/team needs.
Why Ciphr:
We put people first and live our values of Trust, Accountability, Service Excellence and Authenticity - and we’re growing a culture where your personal and professional growth matters.
Benefits that matter:
Private medical (Bupa), dental, health cash plan, life assurance, income protection, pension, 30 days’ holiday + bank holidays, birthday day off, volunteering days, National Trust family membership, cycle to work, tech loans, and more. Plus a Work From Anywhere benefit for up to 4 weeks per tax year (subject to policy).
Apply now:
Bring your enthusiasm, curiosity and growth mindset to a team that’s shaping how UK organisations use people data.
Inclusion at Ciphr: We’re building an inclusive, flexible, supportive culture where individuality is celebrated (including employee resource groups and community). If you need adjustments at any stage, just let us know.
Junior Analytics Engineer in Reading employer: Ciphr
Contact Detail:
Ciphr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Analytics Engineer in Reading
✨Tip Number 1
Network like a pro! Reach out to current employees at Ciphr on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Junior Analytics Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, or data visualisation. This will give you an edge during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on relevant tools like Snowflake, dbt, and Azure DevOps. Practice coding challenges and be ready to discuss how you've used these technologies in past projects.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the Ciphr team and contributing to their data and AI platform.
We think you need these skills to ace Junior Analytics Engineer in Reading
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let your enthusiasm for data and analytics shine through. Share any personal projects or experiences that highlight your curiosity and eagerness to learn—this is what we love to see!
Tailor Your Application: Make sure to customise your application to reflect the specific skills and experiences mentioned in the job description. We want to see how your background aligns with our needs, so don’t be shy about showcasing relevant projects or tools you’ve worked with.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language and avoid jargon unless it’s relevant. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website: Don’t forget 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 shows you’re serious about joining our team!
How to prepare for a job interview at Ciphr
✨Know Your Tools
Familiarise yourself with the tools mentioned in the job description, like Snowflake, dbt, and Azure DevOps. Being able to discuss your experience or knowledge of these platforms will show that you're ready to hit the ground running.
✨Showcase Your Curiosity
Demonstrate your passion for learning by discussing any recent projects or technologies you've explored, especially in AI/ML. This will highlight your growth mindset and adaptability, which are key traits for a Junior Analytics Engineer.
✨Prepare for Technical Questions
Expect technical questions related to Python, SQL, and data visualisation principles. Brush up on your coding skills and be ready to solve problems on the spot, as this will showcase your hands-on experience and analytical thinking.
✨Emphasise Team Collaboration
Ciphr values teamwork, so be prepared to discuss how you've collaborated with others in past projects. Share examples of how you contributed to team success and how you handle feedback, as this will demonstrate your ability to work well within a team.