At a Glance
- Tasks: Lead data engineering projects using Snowflake to transform complex data into actionable insights.
- Company: Join Keyrus, a forward-thinking tech company with a focus on innovation and collaboration.
- Benefits: Enjoy competitive salary, private medical insurance, gym access, and career development opportunities.
- Other info: Work in a dynamic, inclusive environment with excellent growth potential.
- Why this job: Make a real impact by solving business problems and driving digital transformation for clients.
- Qualifications: 8+ years in data engineering with expertise in Snowflake and strong analytical skills.
The predicted salary is between 58000 - 87000 £ per year.
Your role: As a Senior Data Engineer focused on Snowflake, you will work at the intersection of data, technology, and business, helping our clients turn complexity into clarity and insights into impact. You will collaborate with multidisciplinary teams in an international environment and contribute to projects that drive performance, innovation, and sustainable growth.
Job Details
- Location: London, UK (Hybrid, 3 days on-site)
- Contract type: Permanent
- Target start date: May 2026
- Working hours: Full‑time (40 hours per week)
- Compensation: £58k to £87k gross per year
Your Impact
- Understand client needs and lead delivery end‑to‑end – proposing solutions that solve real business problems across ingestion, transformation, governance, and activation.
- Build and manage scalable pipelines using Snowflake, Fivetran, Gong REST APIs, and Snowpipe.
- Configure AWS S3 raw landing zones and Snowflake External Stages to ensure a durable, immutable raw data layer.
- Deal with semi‑structured data and expertly manage JSON/VARIANT payloads in Snowflake, implementing schema‑on‑read patterns to protect against upstream API changes.
- Architect complex dbt models to parse, flatten, and normalise VARIANT data into structured tables.
- Implement logic to merge issuer entities, contact records, and learner profiles across disparate systems to create a Golden Record.
- Build semantic layers for predictive metrics, including Engagement Scores, Sentiment Trends, and Churn Risk.
- Leverage Snowflake Cortex AI for predictive scoring and surfacing insights.
- Maintain governance and security by implementing Role‑Based Access Control (RBAC), PII masking (Dynamic Data Masking), and Row‑Level Security (RLS) across the Snowflake environment.
- Support clients in their data and digital transformation journeys.
What Makes This Role Challenging
- You will work in complex, evolving client environments.
- You are expected to balance delivery quality with pragmatism.
- You will collaborate with diverse profiles across functions and cultures.
- Autonomy increases with seniority – so does responsibility.
What We’re Looking For
Must‑haves
- 8+ years of experience in data engineering.
- Proven experience in Snowflake (expert level: Snowpipe, Access History, Lifecycle Tags, Cortex AI, External Stages).
- Strong hands‑on experience with dbt (expert in modular modelling, documentation, testing).
- Ability to integrate the deployment pipeline using git‑based tools.
- Experience in building ingestion pipelines using AWS S3, Fivetran, Snowpipe, and REST APIs.
- Expertise in cloud‑based architecture (e.g. Azure, AWS).
- Strong analytical and problem‑solving skills, especially in handling JSON/VARIANT and schema‑on‑read patterns.
- Advanced SQL skills (Jinja2 templating is a plus) and working experience with Python for API interactions.
- Demonstrate strong ownership and work independently, taking responsibility for full‑project delivery.
- Ability to communicate clearly with both technical and non‑technical stakeholders.
- Fluency in English.
Nice‑to‑haves
- Familiarity with Databricks for data engineering, notebook workflows, or distributed processing.
- Experience handling CI/CD pipelines for data workloads (e.g., GitHub Actions, GitLab, Azure DevOps, or similar).
- Knowledge of governance practices, including PII handling, RBAC, RLS, and data cataloguing.
- Understanding of reverse ETL concepts and tools.
- Experience with data visualisation tools for analytics and dashboarding (e.g., Qlik, Power BI).
- Experience in consulting environments and mentoring.
- Ability to champion best practices and keep up with innovations and trends on the data landscape.
Salary Ranges
At Keyrus, salary ranges reflect different levels of mastery and impact within the same role—not different job titles.
- Bottom of the range: You meet the core requirements and will need ramp‑up time and support.
- Middle of the range: You are fully autonomous from Day 1 and deliver consistently.
- Top of the range: You are a reference for the role, mentor others, and raise the bar for the team.
Final offers are based on experience, autonomy, scope, and market context, and are discussed transparently during the process.
Benefits
- Competitive holiday allowance.
- Private Medical & Dental Insurance (Bupa).
- Group Life Insurance.
- Gym & fitness discounts via Pluxee (Sodexo).
- On‑site gym access at our London office.
- Access to lifestyle discounts (travel, retail, entertainment & more) via Pluxee (Sodexo).
- Auto‑enrolment pension scheme with Aegon.
- Training & Development via KLX (Keyrus Learning Experience).
- Strong focus on career development and internal mobility.
- Electric & hybrid car scheme via Tusker.
- Annual discretionary bonus, based on individual and company performance.
- Referral bonus for introducing new colleagues.
Equal Opportunity Statement
We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic. Everyone belongs at Keyrus.
Senior Snowflake Data Engineer employer: Keyrus
At Keyrus, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. Our commitment to employee growth is evident through our robust training programmes and focus on internal mobility, ensuring that you can thrive in your career while enjoying competitive benefits such as private medical insurance, gym access, and a generous holiday allowance. Join us to make a meaningful impact in data engineering while working in a supportive and inclusive environment that values diversity and encourages personal development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Snowflake Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Snowflake. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Snowflake and dbt. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Be ready to discuss how you've tackled complex problems, especially with JSON/VARIANT data and cloud architectures. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Snowflake Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Snowflake and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical skills, especially with Snowflake, dbt, and AWS. We love seeing concrete examples of how you've used these tools to solve real business problems in your previous roles.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Keyrus
✨Know Your Snowflake Inside Out
Make sure you brush up on your Snowflake knowledge before the interview. Be ready to discuss your experience with Snowpipe, Access History, and Cortex AI. Prepare specific examples of how you've used these tools to solve real business problems.
✨Showcase Your Data Engineering Skills
Highlight your hands-on experience with dbt and building ingestion pipelines using AWS S3 and Fivetran. Be prepared to explain your approach to handling semi-structured data and implementing schema-on-read patterns, as this will demonstrate your technical expertise.
✨Communicate Clearly with All Stakeholders
Since you'll be working with both technical and non-technical teams, practice explaining complex concepts in simple terms. Think of examples where you've successfully communicated project details to diverse audiences, showcasing your ability to bridge the gap between tech and business.
✨Emphasise Your Problem-Solving Abilities
Prepare to discuss specific challenges you've faced in previous roles and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, focusing on your analytical skills and how they contributed to successful project outcomes.
