Senior Data Engineer

Tribal Tech - The Digital, Data & AI Specialists
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer (AI & MLOps, AWS, Python)

Data Engineer - (Python, SQL, Machine Learning) - Robotics

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Engineer - UK-based, Hybrid Working


My client, a leading SaaS company, is seeking an experienced Senior Data Engineer to join their innovative team. This role offers a unique opportunity to shape the future of data-driven decision-making within a rapidly growing organization.


Overview

As a Senior Data Engineer, you will be responsible for designing, implementing, and maintaining robust data pipelines and infrastructure. You'll work closely with cross-functional teams to deliver scalable solutions that drive business insights and product development.


Salary Range:£70,000 - £90,000 per annum (depending on experience)


Key Responsibilities

  • Develop and maintain ETL/ELT processes using cloud-based technologies (AWS, Azure, or GCP)
  • Design and implement data warehousing solutions using platforms like Snowflake or Azure Synapse Analytics
  • Create and optimize data models for efficient querying and analysis
  • Collaborate with data scientists and analysts to support machine learning initiatives
  • Implement data quality checks and governance processes
  • Contribute to the development of data visualization solutions using tools like Power BI or Tableau
  • Participate in code reviews and mentor junior team members


Required Skills and Experience

  • 5+ years of experience in data engineering roles
  • Strong proficiency in Python and SQL
  • Extensive experience with cloud platforms (AWS, Azure, or GCP)
  • Hands-on experience with big data technologies such as Hadoop, Spark, or Kafka
  • Familiarity with data warehousing concepts and implementation
  • Experience with CI/CD practices and DevOps principles
  • Knowledge of data modeling techniques and best practices
  • Excellent problem-solving and communication skills


Preferred Qualifications

  • Experience with Databricks or similar data processing platforms
  • Familiarity with streaming data architectures
  • Knowledge of data governance and compliance requirements
  • Relevant certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate)



This is an excellent opportunity for a talented Senior Data Engineer to make a significant impact in a dynamic, fast-paced environment. If you're passionate about leveraging cutting-edge technologies to solve complex data challenges, we want to hear from you.

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 AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.