Data Engineering Lead SQL Snowflake

Client Server
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineering Lead: Lakehouse & DataOps

Data Engineering Lead

Data Engineering Manager

Remote Data Engineering Lead — Scale & Analytics

Lead Data Engineer

Senior Data Engineer - Hybrid Cloud & Snowflake Expert

Data Engineering Lead (SQL Snowflake Python) London / WFH to £85k


Are you a skilled data technologist with strong leadership and stakeholder management skills?


You could be progressing your career in a senior, hands-on Data Engineering Lead position at a global tech company that provide data centric software solutions to major blue-chip and government organisations to enable them to discover and analyse data and customer feedback.


What's in it for you:

  • Salary to £85k
  • Bonus
  • Unlimited holiday allowance
  • Flexible working (x1 day a week in London)
  • Private medical insurance as well as well-being benefits
  • Pension and Life Assurance
  • Committees for wellness, charity and volunteering, DE&I
  • Team and company socials


Your role:

As a Data Engineering Lead you will plan and lead data engineering activities across multiple programmes of work to deliver secure, robust and scalable data engineering solutions for complex data analytics products. You'll implement modern data engineering practices, build complex data pipelines and provide guidance to other team members to ensure optimal code performance is achieved, championing best practices.


Beyond this you'll seek to monetise the database, collaborating closely with business leaders.


Location / WFH:

You can work from home most of the time, meeting up with colleagues in the London office twice a week.


About you:

  • You have experience of building data pipelines on cloud platforms, working with a wide variety of data structures such as Data Warehouses and Data Lakes, with Snowflake experience
  • You have advanced SQL knowledge and experience
  • You have Python coding skills
  • You have experience of working in Agile development environments, with a good understanding of DevOps practices, CI/CD, Automation
  • You have commercial acumen and can spot opportunities to innovate and improve, keeping up to date with the latest trends
  • You have technical leadership, coaching and mentoring skills with advanced communication and stakeholder management skills


Apply now to find out more about this Data Engineering Lead (SQL Snowflake Python) opportunity.


At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're an equal opportunities employer whose people come from all walks of life and will never discriminate based on race, colour, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. The clients we work with share our values.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.