At a Glance
- Tasks: Design and develop analytics-ready data models for impactful reporting and decision-making.
- Company: Join a leading EdTech company focused on innovative data solutions.
- Benefits: Enjoy remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on career development.
- Why this job: Make a real difference by transforming data into actionable insights.
- Qualifications: Strong SQL skills and experience in data modelling and analytics.
The predicted salary is between 63000 - 77000 £ per year.
- Analytics Engineer
- Department: Data
- Description
As an Analytics Engineer within the Data Warehouse team, you will design, develop and maintain reusable, analytics-ready data models that support reporting, business intelligence and decision-making across Parent Pay Group.
You will work with complex and sometimes imperfectly documented source systems, translating business requirements into reliable warehouse structures and efficient transformation logic.
You will take ownership of data engineering work from investigation and design through development, testing, deployment and documentation.
Working closely with BI colleagues and stakeholders, you will help create trusted, consistent and scalable data assets that reduce duplicated logic and make reporting development easier, faster and more reliable.
Key Responsibilities
- Design and develop well-structured, reusable and analytics-ready data models within the data warehouse.
- Build and maintain fact and dimension models with clear grain, keys, relationships, business definitions and historical data handling.
- Develop complex SQL queries, stored procedures and views to transform and combine data from multiple sources.
- Investigate unfamiliar or poorly documented source systems to understand relationships, business rules and data-quality considerations.
- Design efficient and maintainable data transformation and loading processes, including incremental load or refresh approaches where appropriate.
- Reconcile source data with warehouse outputs, identifying and resolving data-quality or logic issues.
- Work with BI colleagues to understand reporting, semantic model and Power BI requirements, ensuring warehouse models are practical for downstream use.
- Document data models, transformation logic, assumptions and known limitations clearly and consistently.
- Apply testing, source control and development standards to ensure solutions are robust, maintainable and scalable.
- Manage priorities, dependencies and delivery risks, communicating progress and raising blockers early.
Skills, Knowledge and Expertise
- Strong SQL Server experience, including advanced SQL development, stored procedures, views and performance-aware query design.
- Experience designing and developing data warehouse models for reporting and analytics.
- Good understanding of dimensional modelling concepts, including facts, dimensions, grain, keys and relationships.
- Experience transforming, combining and reconciling data from multiple source systems.
- Ability to investigate complex or poorly documented datasets and establish trusted business logic.
- Understanding of data quality, testing, documentation and maintainable engineering practices.
- Experience working with BI teams, reporting requirements and downstream analytical or semantic models.
- Ability to take ownership of work, manage priorities and deliver to agreed timescales.
- Clear communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.
- Experience supporting Power BI reporting, semantic models or other BI and analytics platforms.
- Experience working in a Saa S, Ed Tech, payments or education-focused environment.
- Knowledge of source control, deployment processes and data engineering development standards.
- Experience improving existing data warehouse logic, reducing duplication and increasing model reusability.
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Analytics Engineer employer: ParentPay Group
At ParentPay Group, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a Payments Product Owner, you will benefit from a collaborative environment that prioritises user-centric delivery, alongside ample opportunities for professional growth and development. Located in a vibrant area, we offer a range of employee benefits designed to support your well-being and career progression, making us an exceptional employer for those seeking meaningful and rewarding work.
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We think this is how you could land Analytics Engineer
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We think you need these skills to ace Analytics Engineer
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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Craft a Tailored Cover Letter:For a full-time role at ParentPay Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ParentPay Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at ParentPay Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ParentPay Group!
✨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.
