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- Tasks: Lead the design of analytics-ready data models and mentor your team.
- Company: Join a growing analytics engineering function in a dynamic environment.
- Benefits: Competitive salary up to £78,000, remote work options, and professional growth.
- Why this job: Shape the future of data analytics and make a real impact.
- Qualifications: Expert SQL and PySpark skills with experience in modern data platforms.
- Other info: Opportunity for technical leadership and career advancement.
The predicted salary is between 78000 - 78000 £ per year.
This is a high impact Senior Analytics Engineer role within a growing analytics engineering function, sitting at the heart of a major Lakehouse transformation. You will play a key role in shaping how trusted, analytics ready data is modelled and served across a complex organisation, while also providing technical leadership and mentoring within the team.
ROLES AND RESPONSIBILITIES:
- Lead the design and delivery of curated, analytics ready data models within a Lakehouse environment
- Own dimensional and semantic modelling to enable consistent, trusted reporting across the business
- Build and maintain complex SQL and PySpark transformation pipelines using Databricks
- Drive data quality, testing, reliability and performance across the curated or gold data layer
- Work closely with data engineers, BI teams and business stakeholders to translate complex requirements into scalable datasets
- Provide technical leadership through design reviews, mentoring and setting analytics engineering standards
- Contribute to CI/CD and modern engineering best practices across the data platform
YOUR SKILLS AND EXPERIENCE:
- Strong commercial experience as an Analytics Engineer within a modern data platform or Lakehouse architecture
- Expert level SQL and strong hands on PySpark capability
- Proven experience designing and owning dimensional data models for analytics and reporting
- Experience working with Databricks, including pipelines and governed data environments
- Solid understanding of engineering best practices, including testing, version control and deployment
- Confidence mentoring others and taking ownership of technical direction
Senior Analytics Engineer (12 month FTC) employer: Harnham - Data & Analytics Recruitment
Contact Detail:
Harnham - Data & Analytics Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer (12 month FTC)
✨Tip Number 1
Network like a pro! Reach out to folks in the analytics space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL and PySpark projects. We want to see what you can do, so make sure to highlight any cool data models or pipelines you've built.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with Lakehouse architecture. We recommend practising common interview questions and even doing mock interviews with friends.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Analytics Engineer (12 month FTC)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your expertise in SQL, PySpark, and any relevant projects you've worked on that align with the role.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for the Senior Analytics Engineer role. Share specific examples of how you've led data modelling projects or mentored others in your previous roles.
Showcase Your Technical Skills: Don’t shy away from detailing your technical prowess! Include any relevant certifications or projects that demonstrate your experience with Databricks and modern data platforms.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Harnham - Data & Analytics Recruitment
✨Know Your Data Inside Out
Make sure you’re well-versed in the specifics of data modelling and analytics engineering. Brush up on your SQL and PySpark skills, and be ready to discuss how you've designed and owned dimensional data models in the past. This will show that you can hit the ground running.
✨Showcase Your Technical Leadership
Prepare examples of how you've provided technical leadership in previous roles. Think about times when you’ve mentored others or led design reviews. This is crucial for demonstrating your ability to guide a team and set standards in analytics engineering.
✨Understand the Lakehouse Architecture
Familiarise yourself with Lakehouse environments and how they differ from traditional data platforms. Be ready to discuss your experience with Databricks and how you’ve built and maintained transformation pipelines. This knowledge will highlight your fit for the role.
✨Communicate Clearly with Stakeholders
Practice explaining complex technical concepts in simple terms. You’ll need to work closely with BI teams and business stakeholders, so being able to translate their requirements into scalable datasets is key. Show that you can bridge the gap between technical and non-technical teams.