At a Glance
- Tasks: Develop and troubleshoot data workflows using Spark, Scala, and Python.
- Company: HelloKindred, a leader in staffing marketing and tech roles.
- Benefits: Hybrid work setup, competitive salary, and inclusive culture.
- Other info: Opportunity for career growth in a supportive environment.
- Why this job: Join a dynamic team and make an impact on large-scale financial datasets.
- Qualifications: Strong skills in data engineering and experience with Apache Airflow.
The predicted salary is between 54000 - 66000 £ per year.
HelloKindred are specialists in staffing marketing, creative and technology roles, offering a range of talent solutions that can be delivered on-site, remotely or hybrid. Our vision is to make work accessible and people’s lives better by disrupting traditional employment barriers – connecting ambitious talent to flexible opportunities with trusted brands.
Anticipated Contract End Date/Length: December 31, 2026
Work set up: Hybrid (2–3 days per week in office)
Clearance required: BPSS checks. Candidates must be eligible for BPSS clearance.
Our client in the Information Technology and Services industry is looking for a Data Engineer with strong Spark, Scala, and Python skills to develop, maintain, and troubleshoot data orchestration workflows and reusable engineering components. The role will support the processing, transformation, validation, and delivery of large-scale financial datasets, while contributing to platform engineering, production support, monitoring, automation, and operational resilience. The successful candidate will work across application, platform, database, infrastructure, and downstream teams to maintain reliable data processes and ensure compliance with technology, security, and change standards.
Responsibilities:
- Develop, maintain, and troubleshoot data orchestration workflows using Apache Airflow for extract generation, data publishing, feed delivery, and operational batch processes.
- Build and support reusable engineering components using Python, Scala, and Sharedview Spark to process, transform, and validate large-scale financial datasets.
- Design, write, and optimize SQL/PostgreSQL and Starburst/Trino queries for metadata processing, data validation, reconciliation, and operational investigation.
- Support Output Gateway production issues, including failed DAGs, delayed extracts, missing files, data mismatches, checksum failures, logs, status updates, and downstream delivery exceptions.
- Contribute to platform engineering and release activities using GitLab, Docker, and controlled CI/CD practices across DEV, UAT, and production-like environments.
- Enhance monitoring, logging, alerting, audit tracking, and automation to improve operational stability, supportability, and evidence for control processes.
- Work with application, platform, database, infrastructure, and downstream teams to diagnose issues end-to-end and implement safe, controlled fixes.
- Maintain a strong risk and control mindset by ensuring changes are tested, reviewed, documented, and released in accordance with technology, security, and change standards.
Qualifications:
- Strong skills and experience in data engineering using Spark, Scala, and Python.
- Experience developing, maintaining, and troubleshooting Apache Airflow workflows for data orchestration and operational batch processes.
- Hands-on experience building reusable engineering components to process, transform, and validate large-scale financial datasets.
- Proficiency in SQL and PostgreSQL, including query design, optimization, metadata processing, data validation, and reconciliation.
- Experience supporting production data workflows and troubleshooting failed DAGs, delayed extracts, missing files, data mismatches, checksum failures, and downstream delivery exceptions.
- Familiarity with GitLab, Docker, and controlled CI/CD practices across development, UAT, and production-like environments.
- Understanding of monitoring, logging, alerting, audit tracking, and automation to improve operational stability and supportability.
- Ability to collaborate with application, platform, database, infrastructure, and downstream teams to diagnose and resolve technical issues.
- Strong awareness of risk, controls, testing, documentation, and technology, security, and change standards.
Desirable Skills / Preferred Qualifications:
- Experience with Starburst/Trino, AWS S3 concepts, and distributed query behaviour for large-dataset validation and troubleshooting.
- Exposure to React JS or API-driven operational user interfaces for configuration, monitoring, and support workflows.
- Familiarity with OpenShift, Kubernetes, Helm, or container platform deployments in enterprise environments.
- Understanding of financial data controls, auditability, reconciliation, data lineage, operational resilience, and data quality expectations.
All your information will be kept confidential according to EEO guidelines. Candidates must be legally authorized to live and work in the country where the position is based, without requiring employer sponsorship. HelloKindred is committed to fair, transparent, and inclusive hiring practices. We assess candidates based on skills, experience, and role-related requirements. We appreciate your interest in this opportunity. While we review every application carefully, only candidates selected for an interview will be contacted. HelloKindred is an equal opportunity employer. We welcome applicants of all backgrounds and do not discriminate on the basis of race, colour, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic under applicable law.
Data Engineer in Glasgow employer: HelloKindred
HelloKindred is an exceptional employer that values innovation and collaboration, offering a dynamic work culture where employees can thrive. With a strong focus on professional development, team members have access to ongoing training and certification opportunities, ensuring they stay at the forefront of technology. The hybrid work model promotes a healthy work-life balance, making it an ideal place for those seeking meaningful and rewarding employment in the heart of the UK.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Glasgow
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like HelloKindred!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at HelloKindred.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like HelloKindred.
✨Apply Directly through Our Website
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We think you need these skills to ace Data Engineer in Glasgow
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at HelloKindred, 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 HelloKindred. 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 HelloKindred
✨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!
✨Showcase Your Projects
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 HelloKindred!
✨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.
