At a Glance
- Tasks: Dive deep into data analysis and help shape innovative data products.
- Company: Join a dynamic team in a fast-paced, hybrid work environment.
- Benefits: Enjoy flexible working, competitive pay, and opportunities for growth.
- Other info: Collaborate with engineering teams and thrive in a supportive culture.
- Why this job: Make an impact by transforming raw data into valuable insights.
- Qualifications: Strong SQL skills and a passion for data analysis required.
The predicted salary is between 35000 - 45000 € per year.
Location: Edinburgh or Manchester (Hybrid - 1 day onsite per week, Wednesdays)
Type: Contract
Overview
We're looking for a highly data-focused Data Analyst to support the development of data products within a modern AWS-based architecture. This role is centred on deep data analysis and discovery (70%), alongside logical data modelling (30%), helping shape how raw data is standardised, structured, and consumed.
You'll work closely with engineering teams, translating business needs into technical user stories and supporting the evolution of scalable data solutions.
Key Responsibilities
- Data Analysis & Discovery (70%)
- Conduct detailed data discovery across multiple datasets, identifying structure, quality, and relationships
- Investigate and interrogate data to uncover insights and anomalies
- Work hands-on with SQL to query and analyse large datasets
- Support data grouping, profiling, and exploration activities
- Collaborate with stakeholders to define data requirements and translate these into actionable outputs
- Contribute to the creation and refinement of data products
- Data Modelling (30%)
- Develop and maintain logical data models (LDM)
- Map and align data structures to Federated Data Models (FDM)
- Support data standardisation processes, particularly from raw data sources
- Work closely with architecture and engineering teams on data product architecture
- Ensure consistency and best practice across data modelling and design
Technical Environment & Experience
- Strong SQL skills (essential)
- Experience working with AWS (including S3 buckets)
- Exposure to data product architecture
- Understanding of raw data ingestion and standardisation
- Experience collaborating with data engineering / extract engineering teams
- Ability to write and refine technical user stories
Skills & Profile
- Highly analytical with a strong focus on data investigation and discovery
- Comfortable working in data-heavy, complex environments
- Strong understanding of logical data modelling principles
- Ability to bridge the gap between business needs and technical delivery
- Proactive, detail-oriented, and confident working with ambiguous datasets
Additional Information
- Hybrid working: 1 day per week onsite (Wednesday) in either Edinburgh or Manchester
- Flexible engagement options available
- Fast-paced, delivery-focused environment
Data analyst / analyst in Manchester employer: Lorien
Join a dynamic and innovative team as a Data Analyst in either Edinburgh or Manchester, where you'll thrive in a hybrid work environment that promotes flexibility and collaboration. Our company fosters a culture of continuous learning and growth, offering ample opportunities for professional development while working on cutting-edge data products within a modern AWS architecture. With a focus on meaningful data analysis and a supportive atmosphere, we empower our employees to make impactful contributions and advance their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data analyst / analyst in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising your SQL skills and brushing up on data modelling concepts. We recommend running through common interview questions and even doing mock interviews with friends to build your confidence.
✨Tip Number 3
Showcase your analytical skills by creating a portfolio of projects. Whether it's a personal project or something from a previous job, having tangible examples of your work can really impress hiring managers.
✨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 Data analyst / analyst in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Analyst role. Highlight your SQL skills and any experience with AWS, as these are key for us. Use specific examples that showcase your analytical abilities and how you've tackled data challenges in the past.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you're passionate about data analysis and how you can contribute to our team. Mention your experience with data discovery and modelling, and don’t forget to show a bit of personality!
Showcase Relevant Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we want to see how you've applied your skills in real-world scenarios, especially with large datasets.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly. Plus, it shows you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Lorien
✨Know Your SQL Inside Out
Since strong SQL skills are essential for this role, make sure you brush up on your querying techniques. Prepare to discuss specific queries you've written in the past and how they helped uncover insights from large datasets.
✨Understand Data Modelling Principles
Familiarise yourself with logical data modelling principles and be ready to explain how you've applied them in previous projects. Think about examples where you mapped data structures or contributed to data standardisation processes.
✨Showcase Your Analytical Skills
Be prepared to discuss your approach to data analysis and discovery. Share specific instances where you identified anomalies or insights from complex datasets, and how those findings impacted business decisions.
✨Bridge Business and Technical Needs
This role requires translating business needs into technical user stories. Think of examples where you've successfully collaborated with stakeholders to define data requirements and how you ensured those were actionable for engineering teams.
