Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Snowflake Data Engineer - Remote - £competitive

London
2 days ago
Create job alert

Senior Snowflake Data Engineer - Remote - £competitive

About the Role
We are looking for an experienced Senior Snowflake Data Engineer to join a dynamic team working on cutting-edge data solutions. This is an exciting opportunity to design, build, and optimise high-performance data pipelines using Snowflake, dbt, and modern engineering practices. If you are passionate about data engineering, test-driven development, and cloud technologies, we'd love to hear from you.

Key Responsibilities

Design, develop, and optimise scalable data pipelines in Snowflake.
Build and maintain dbt models with robust testing and documentation.
Apply test-driven development principles for data quality and schema validation.
Optimise pipelines to reduce processing time and compute costs.
Develop modular, reusable transformations using SQL and Python.
Implement CI/CD pipelines and manage deployments via Git.
Automate workflows using orchestration tools such as Airflow or dbt Cloud.
Configure and optimise Snowflake warehouses for performance and cost efficiency.

Required Skills & Experience

7+ years in data engineering roles.
3+ years hands-on experience with Snowflake.
2+ years production experience with dbt (mandatory).
Advanced SQL and strong Python programming skills.
Experience with Git, CI/CD, and DevOps practices.
Familiarity with ETL/ELT tools and cloud platforms (AWS, Azure).
Knowledge of Snowflake features such as Snowpipe, streams, tasks, and query optimisation.

Preferred Qualifications

Snowflake certifications (SnowPro Core or Advanced).
Experience with dbt Cloud and custom macros.
Exposure to real-time streaming (Kafka, Kinesis).
Familiarity with data observability tools and BI integrations (Tableau, Power BI).

What We Offer

Opportunity to work with modern data technologies and large-scale architectures.
Professional development and certification support.
Collaborative, engineering-focused culture.
Competitive salary and benefits package.

Interested?
Apply now with your CV highlighting your Snowflake, dbt, and DevOps experience

Related Jobs

View all jobs

Senior Snowflake Data Engineer - Remote - £competitive

Senior Data Engineer

Lead Data Engineer SQL Python

Senior Data Engineer

(INV) Senior Consultant, Data Engineer, AI&Data, UKI

(INV) Senior Consultant, Data Engineer, AI&Data, UKI

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.