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- Tasks: Lead the design of data models and transform datasets for trusted insights.
- Company: Join a forward-thinking company focused on data and analytics.
- Benefits: Remote work, flexible schedules, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving innovation in data engineering.
- Why this job: Make a real impact in a growing Lakehouse environment with visibility across the business.
- Qualifications: Experience as an Analytics Engineer with strong SQL and PySpark skills.
The predicted salary is between 60000 - 75000 £ per year.
This Senior Analytics Engineer role stands out as a chance to play a key part in a large scale Lakehouse programme, sitting at the intersection of engineering, analytics and the wider business. You will take real ownership of curated data models, shape how data is structured and served across the organisation, and influence best practice as the analytics engineering capability continues to grow.
Data and analytics are a strategic priority, with ongoing investment into a modern cloud based data platform. Engineering teams are expanding as part of a broader transformation, creating genuine opportunities to have impact and influence.
You will join a growing analytics engineering team and play a critical role in the Lakehouse environment:
- Leading the design and delivery of curated, analytics ready data models within the Lakehouse
- Owning the transformation from enriched to curated datasets, enabling trusted reporting and insight
- Developing and maintaining robust SQL and PySpark transformation pipelines in Databricks
- Embedding data quality, testing, reliability and performance into the curated layer
- Working closely with data engineers, BI teams and business stakeholders to translate complex requirements
- Contributing to CI/CD processes and wider engineering best practice across the data platform
Strong commercial experience as an Analytics Engineer within a modern data platform is required, along with excellent data modelling capability, including dimensional and semantic modelling, advanced SQL skills, and strong hands on experience with PySpark. A solid grounding in engineering best practices, testing and data quality is essential.
Flexible by choice working, supporting different schedules and work life balance is encouraged. This is an opportunity to shape a critical data programme with real visibility across the business.
If you are a Senior Analytics Engineer looking to make an impact in a growing Lakehouse environment, apply now to find out more.
Senior Analytics Engineer (Remote Working) employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer (Remote Working)
✨Tip Number 1
Network like a pro! Reach out to current employees in similar roles or teams on LinkedIn. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Showcase your skills in action! If you’ve got a portfolio of projects or case studies, share them during interviews. It’s a great way to demonstrate your expertise in SQL and PySpark.
✨Tip Number 3
Prepare for those tricky questions! Brush up on common analytics engineering scenarios and be ready to discuss how you’d tackle data quality and transformation challenges.
✨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 and shows you’re genuinely interested in joining our team.
We think you need these skills to ace Senior Analytics Engineer (Remote Working)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Analytics Engineer role. Highlight your experience with SQL, PySpark, and data modelling to show us you’re the perfect fit for our Lakehouse programme.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re excited about this opportunity. Share specific examples of how you've contributed to analytics projects in the past and how you can bring that expertise to our growing team.
Showcase Your Technical Skills: Don’t shy away from detailing your technical prowess! We want to see your hands-on experience with Databricks and CI/CD processes. Be specific about the tools and technologies you’ve used to deliver impactful data solutions.
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 don’t miss out on any important updates during the process!
How to prepare for a job interview at Harnham
✨Know Your Data Models
Make sure you brush up on your data modelling skills, especially dimensional and semantic modelling. Be ready to discuss how you've designed and delivered curated data models in the past, as this will show your understanding of the role's key responsibilities.
✨Showcase Your SQL and PySpark Skills
Prepare to demonstrate your advanced SQL skills and hands-on experience with PySpark. You might be asked to solve a problem or optimise a query, so practice common scenarios and be ready to explain your thought process.
✨Understand the Lakehouse Concept
Familiarise yourself with the Lakehouse architecture and its benefits. Be prepared to discuss how it differs from traditional data warehouses and how you can contribute to its success within the organisation.
✨Emphasise Collaboration
This role involves working closely with data engineers, BI teams, and business stakeholders. Highlight your experience in translating complex requirements and collaborating across teams, as this will demonstrate your ability to thrive in a cross-functional environment.