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

Apply Now

Job in Germany: Data Engineer - Data Warehouse & ETL (w/m/d)

ING Deutschland
uk
4 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst Project Intern (TikTok Shop - FMCG) - 2025 Start (BS/MS)

Data Analyst Project Intern (TikTok Shop - User Growth) - 2025 Start (BS/MS)

Data Analyst / BI Developer

Data Engineering Manager

Data Engineer - Data Warehouse & ETL (f/m/d) Data Engineer - Data Warehouse & ETL (f/m/d)
at the Frankfurt location

Do you know what data needs to become really useful? Do you use your expertise, team spirit and communication skills to create solutions with real added value? That's perfect! In our corporate culture, we value exactly that: respectful team play, personal and professional development and working together as equals. Apply now with your CV, your team is looking forward to hearing from you.

Your tasks

  • Thanks to you, our data has a safe home port: you design, develop, implement and maintain data warehouse solutions and architectures that meet all requirements.
  • You will then plan and develop sophisticated ETL processes with which we integrate data from a wide variety of sources and ensure that it is structured and available to us at all times.
  • To ensure that our data grows beyond itself, you create sophisticated data models for excellent consistency and quality, also lend a hand in data analysis and validation and thus support our business decisions in the long term.
  • And, of course, you will continuously work on driving our database and ETL performance to the top, optimizing where possible, recording everything in comprehensible technical documentation and liaising with colleagues and specialist departments from across the bank.

Your profile

  • Completed studies in (business) informatics or a comparable qualification
  • Extensive practical experience in the development and maintenance of data warehouses and ETL processes as well as in dealing with Microsoft Azure
  • Sound knowledge of SQL and ETL tools (e.g. DataStage)
  • Know-how in data modelling and analysis as well as performance tuning and optimization of database and ETL processes
  • Communication skills, a structured way of working and enjoy working in a team
  • An innovative spirit and a sense for sustainable solutions
  • Very good written and spoken English; German is a plus

Look forward to numerous benefits

  • Company pension scheme, capital-forming benefits, free Germany ticket & Bike LeasING, company restaurant
  • Hybrid working model: In addition to working in the office, you can also work remotely - within the framework of company, legal and regulatory requirements.
  • Individual working time models, sabbatical, subsidization of care & childcare costs
  • Individual budgets for personal development and health plus a personal equipment budget for your mobile workplace

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.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.