Krystal Clarity
Data Engineer

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Job Title: Data Engineer
Company: Krystal Clarity
Location: London/Remote
Job Type: Full-Time
Salary: £40k - £50k
About Us:
Krystal Clarity is a rapidly emerging data engineering consultancy and Databricks partner that helps businesses leverage data to achieve their strategic objectives. As a lean, fast-paced, and dynamic company, we are looking for an ambitious Data Engineer who thrives in an entrepreneurial environment and seeks to be part of the foundational team driving the company's growth and success.
Position Overview:
We are seeking a Mid Level Data Engineer with 2 to 4 years of experience in data engineering, with strong exposure to Azure, Databricks and Python. You'll work closely with senior engineers on real-world client projects, designing, building, and deploying data pipelines in the cloud. This role is perfect for someone looking to sharpen their technical skills, work in a collaborative consultancy environment, and take ownership of impactful work.
Responsibilities:
- Design, build, and optimise scalable data pipelines using Databricks (PySpark, SQL, Delta Lake) on Azure.
- Build ingestion from REST APIs, including incremental and near-real-time load patterns, alongside managed connectors such as Lakeflow Connect and Azure Data Factory.
- Collaborate with senior engineers to understand requirements and implement solutions for clients.
- Work directly with client stakeholders, including face-to-face: gathering requirements, presenting solutions and communicating progress to technical and non-technical audiences.
- Write clean, maintainable code in Python, applying best practices for testing and code quality.
- Use AI coding assistants (Claude Code, Cursor, Codex or similar) day to day to accelerate development, testing and documentation, while maintaining code quality.
- Contribute to CI/CD workflows using GitHub Actions and Azure Pipelines, including automation of infrastructure and deployments.
- Use Terraform and Declarative Automation Bundles to manage infrastructure as code, alongside scripting tools (Bash, PowerShell).
- Apply strong data governance and quality practices, including Unity Catalog, RBAC and PII handling, to ensure data integrity.
- Document solutions, pipelines, and design decisions for future maintainability.
- Continuously learn and explore new tools, frameworks, and best practices in data engineering.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements:
- Bachelor's or Master's in a STEM subject (Computer Science, Maths, Physics, Engineering,...).
- 2 to 4 years of experience as a data engineer working on Azure Databricks or in the Azure/AWS ecosystem.
- Hands-on experience with Python (PySpark strongly preferred) and strong SQL skills is required.
- Hands-on experience using AI coding tools (Claude Code, Cursor, Codex or similar) in real development workflows, with judgement on when and how to apply them.
- Experience with infrastructure-as-code, ideally Terraform, is required.
- Familiarity with CI/CD workflows and tools like GitHub Actions or Azure Pipelines.
- Working knowledge of Unity Catalog and data governance fundamentals.
- Experience ingesting data from REST APIs and various third-party systems.
- Experience with the wider Azure data ecosystem (Data Factory, Storage, Event Hub) is desirable.
- Expertise in other relevant technologies is desirable: Lakeflow Connect, Declarative Pipelines, Databricks Apps, Vector Search or MLOps, dbt, Snowflake, Debezium/Kafka/Streaming, Power BI.
- Ability to work collaboratively in a small, fast-moving team.
- Strong communication and stakeholder-management skills, with the confidence to work with clients face-to-face from day one and the knack for simplifying complex topics.
- Resilience to thrive in a dynamic environment, adeptly managing multiple projects.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
What We Offer:
- The opportunity to join a consultancy in its growth stage and directly shape its success.
- Hands-on experience across diverse client projects with mentorship from senior engineers.
- Competitive salary and benefits package.
- Flexibility to work remotely, with occasional in-person collaboration.
To Apply:
Please send your CV and a cover letter explaining your interest in the role to recruitment@krystalclarity.com.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location