At a Glance
- Tasks: Lead Snowflake implementation, manage data pipelines, and ensure data governance.
- Company: Join KX, a forward-thinking tech company focused on data innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be part of a small, dynamic team with direct access to senior leadership.
- Why this job: Shape the future of data at KX and influence key business decisions.
- Qualifications: Experience with Snowflake, data governance, and strong analytical skills.
The predicted salary is between 80000 - 100000 £ per year.
KX is hiring a Lead Snowflake Data Engineer to join a lean, four-person Enterprise Applications team reporting into the Head of Enterprise Applications. This is the critical hire that takes ownership of Snowflake as an internal capability, inheriting an in-progress implementation from third-party partners, validating what’s been built, and carrying the platform forward towards a single Business 360 view unifying Finance, Revenue, and People data. This is a hands-on, end-to-end role spanning ingestion through to certified metrics, with direct exposure to senior leadership and a mandate to shape how KX uses data and AI to make faster, more accurate decisions.
Requirements
- Own data ingestion pipelines into Bronze through Workato, and maintain the full Medallion stack: Bronze (raw), Silver (cleansed), Gold (dimensional models and marts), and Platinum (semantic layer and certified metrics).
- Deliver data governance across all Medallion layers: RBAC with least-privilege access, dynamic data masking, column-level security, data catalogue, business glossary, and lineage from source to semantic layer, aligned to GDPR, SOC 2, and ISO 27001.
- Implement data quality and observability: tests, freshness SLAs, anomaly detection, alerting, and clear escalation paths when issues arise.
- Drive the Snowflake capability roadmap: evaluate and pilot dynamic tables, streams and tasks, Snowpark, Cortex, and Marketplace; identify where Cortex and LLM functions can reduce manual effort for business users within KX’s AI governance framework.
- Manage platform performance, cost, and reliability: sizing, clustering, materialisation, and query tuning, and maintain documentation, lineage, and standards for everyone who works with Snowflake.
- Sit on the Data Governance Work Group (chaired by the CIO), contributing to data ownership, metric certification, and schema change approvals.
Lead Snowflake Data Engineer in London employer: KX
KX is an exceptional employer for the Lead Snowflake Data Engineer role, offering a dynamic work environment where innovation and collaboration thrive. With a focus on employee growth, KX provides opportunities to shape data strategies that drive impactful business decisions while working closely with senior leadership. The company's commitment to a lean team structure fosters a culture of agility and creativity, making it an ideal place for professionals eager to make a meaningful contribution in the tech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Snowflake Data Engineer in London
✨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 KX!
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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 KX.
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When you find a suitable opening like Lead Snowflake Data Engineer at KX, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Snowflake Data Engineer in London
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 KX, 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 KX. 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 KX
✨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 KX!
✨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.
