Senior Data Architect

Essen
9 months ago
Applications closed

Related Jobs

View all jobs

Naimuri - Senior Data Scientist

Senior Data Scientist

Senior Data Scientist - Hertfordshire, HP2 4YL

Senior Data Scientist

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

Senior Data Scientist - Optimisation

Senior Data Engineer / Architect - Essen - Germany
Hybrid 2x per month on-site

Are you a data expert ready to shape the future of enterprise-scale platforms? Electus is proud to partner with a cutting-edge AI/ML analytics company to hire a Senior Data Engineer/Architect who will play a pivotal role in transforming their data architecture and engineering capabilities.

🌟 Why This Role Stands Out
Shape the future of a modern data platform from the ground up.
Autonomy & trust – bring your ideas and lead with impact.
Flat hierarchy – collaborate directly with decision-makers.
Work with the latest tech – AWS, Kubernetes, Docker, Spark, and more.🧠 What You’ll Be Doing
Collaborate with stakeholders, data scientists, and engineers to design scalable, high-performance data solutions.
Build and maintain robust data pipelines and ETL processes.
Design and evolve data models for efficient storage and retrieval.
Lead the implementation of Big Data applications and analytical tools.
Champion data governance, security, and quality standards.
Mentor junior engineers and foster a culture of technical excellence.🎯 What Success Looks Like in Year One
You’ll have solved key data architecture pain points in collaboration with the data team.
Delivered scalable, maintainable solutions that support business growth.
Introduced best practices and new technologies that elevate the platform’s performance.✅ What We’re Looking For
Proven experience designing and building complex data solutions in enterprise environments.
Skills in Python or Java.
Deep SQL expertise - query performance analysis and relational databases
Hands-on experience with AWS, Kubernetes, and Docker.
Solid understanding of Agile & Scrum methodologies and software engineering principles.
Excellent communication and problem-solving skills.💡 Bonus Points For
Experience with Apache StarRocks, Databricks, or Hive.
Familiarity with Iceberg, Hudi, or Delta Lake.
Knowledge of Spark, Flink, or Scala.🎓 Qualifications
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.👤 Who Thrives Here
You’re a collaborative leader who enjoys mentoring and sharing knowledge.
You thrive in fast-paced, evolving environments.
You care deeply about data quality, security, and performance.
You’re always learning and love applying new technologies.📩 Ready to Apply? If you're ready to take the lead in shaping a next-gen data platform, we’d love to hear from you. Apply now or reach out to Electus for a confidential conversation

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.