Snowflake Data Engineer - Outside IR35 - Hybrid 3 days a week

Tenth Revolution Group
London
1 month ago
Applications closed

Related Jobs

View all jobs

AWS Data Engineer - Snowflake Cortex (Contract)

Data Engineer

Urgent | Contract Senior Data Engineer - Azure + Databricks + Snowflake

Senior Data Engineer

Lead Data Engineer (AWS & Snowflake)

Senior Data Engineer

Snowflake Data Engineer - Outside IR35 - Hybrid (3 days a week)About the Role

We are seeking a skilled Snowflake Data Engineer to design, build, and optimize scalable data solutions within our modern cloud data platform. You will play a key role in developing high-performance data pipelines, implementing data models, and enabling advanced analytics using Snowflake.

The ideal candidate has strong experience in cloud-based data warehousing, ETL/ELT development, and performance optimization, along with a passion for building reliable, scalable data systems.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines using Snowflake

  • Build and optimize data models (star/snowflake schema) to support business intelligence and analytics

  • Develop ELT processes using SQL, stored procedures, and cloud-native tools

  • Integrate data from multiple sources (APIs, databases, streaming platforms) into Snowflake

  • Implement data governance, security, masking, and role-based access controls

  • Monitor performance and optimize queries, clustering, and warehouse configurations

  • Collaborate with analytics, BI, and data science teams to deliver high-quality datasets

  • Support CI/CD processes and infrastructure-as-code for d...

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.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.