At a Glance
- Tasks: Analyse complex data, automate tasks with Python, and support engineering decisions.
- Company: Join a public sector client focused on innovative data solutions.
- Benefits: Remote work, competitive pay, and potential for contract extension.
- Other info: Agile environment with opportunities for professional growth.
- Why this job: Make a real impact by solving data challenges in a dynamic team.
- Qualifications: 5+ years experience in data analysis, strong Python and SQL skills required.
The predicted salary is between 45000 - 55000 £ per year.
We are supporting a public sector client in hiring a Data Analyst to join a multidisciplinary data team working on a complex, multi-source data platform. This is a hands-on analytical and coding role focused on profiling and assessing data ingested from multiple source systems, identifying where platform functionality does not fully cover or accurately process incoming data, and producing clear, evidence-based findings that directly inform engineering decisions.
The source data is accepted as provided and cannot be modified. The successful candidate will develop a deep understanding of that data, its structure, patterns and edge cases, and work closely with data engineers to prioritise and address coverage gaps and processing issues. A core part of this role involves writing Python code to automate analytical tasks, generate and manipulate YAML configuration files and support broader data engineering workflows.
This role suits an experienced Senior or Mid-Level Data Analyst with at least 5 years of experience, strong hands-on coding ability across Python and SQL, and a sharp, methodical analytical mindset comfortable working at pace in an Agile, multidisciplinary environment.
Key Responsibilities- Profile data ingested from multiple source systems, developing a thorough understanding of structure, content, patterns and edge cases.
- Identify and document gaps where platform functionality does not fully cover, correctly interpret or accurately process the data being received.
- Investigate discrepancies between expected and actual data processing outcomes, clearly articulating where platform logic falls short.
- Produce clear, evidence-based findings that enable data engineers to prioritise and address coverage gaps and processing issues.
- Write Python scripts to automate data analysis tasks, generate YAML configuration files and support repeatable, config-driven workflows.
- Develop and maintain SQL queries for exploratory analysis, data profiling and validation of processing outputs.
- Define and document data coverage rules, assessment criteria and known platform limitations in collaboration with technical and business teams.
- Contribute to documentation of data definitions, data lineage and known processing constraints across the platform.
- Participate in Agile delivery ceremonies and contribute to continuous improvement of team practices.
- Strong Python proficiency with the ability to write clean, maintainable scripts for automation, data analysis and YAML file generation and parsing.
- Strong SQL skills including complex queries, joins, aggregations, window functions and performance optimisation.
- Solid understanding of YAML structure and experience working with YAML-based configuration files using Python libraries.
- Understanding of medallion architecture, Azure Data Lake Storage and Databricks, with a focus on Parquet files and Delta tables.
- Experience working with Azure cloud services including Azure Synapse Analytics.
- Demonstrated experience in data profiling across large, complex or multi-source datasets, identifying patterns, anomalies and edge cases.
- Ability to interpret and work with data schemas and data dictionaries.
- Strong analytical mindset with exceptional attention to detail and a methodical approach to problem-solving.
- Confident communicator able to present technical findings clearly to non-technical stakeholders.
- Familiarity with data warehouse or data lake architectures and modern data platform design principles.
- Experience working within configuration-driven or parameter-driven data pipeline frameworks.
- Knowledge of data governance principles and metadata management practices.
- Experience within a regulated or public sector data environment.
- Familiarity with CI/CD workflows and version control using Git and Azure DevOps.
Data Analyst (SC Cleared) in England employer: Montash
Montash is an excellent employer that values innovation and collaboration, providing a dynamic work environment in Glasgow. With a strong focus on employee growth, we offer extensive training and development opportunities, alongside a flexible hybrid working model that promotes work-life balance. Join us to be part of a forward-thinking team dedicated to delivering impactful technology solutions in the public sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst (SC Cleared) in England
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Montash before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Montash.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Montash.
We think you need these skills to ace Data Analyst (SC Cleared) in England
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Montash, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Montash, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Montash’s attention and show the tangible impact of your work.
How to prepare for a job interview at Montash
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Montash.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Montash.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Montash.
