​Peer inside the data engineering market and you’ll be spoilt for contradictions. Increasingly complex tools are met with growing demand for simple solutions, salary hikes face off against a surge in automation, and layoffs are juxtaposed with skill shortages.

The German market, a stronghold of innovation, is a prime example. Despite boasting one of the largest IT markets anywhere, decision-makers aren’t convinced the nation is prepared for a digital overhaul – as many as 95% of executives say Germany lags behind, as per a report from the European Center for Digital Competitiveness.

That said, Germany’s position as a global leader in industrie 4.0 spotlights a crucial paradox. While it excels in smart manufacturing and SaaS, it faces significant hurdles in its transformation journey, representing a unique slew of challenges and opportunities in the data engineering market.

Changes

One aspect is clear – the data engineering landscape is undergoing a seismic shift, revealing a somewhat fragmented market. It’s largely thanks to technological innovation, shifts in corporate governance, and the evolving demands of today’s businesses, including the call for:

• Lakehouse architecture, no-code development, and decentralisation (data mesh)

• Generative AI integrations

• Leaner teams

• Workforce diversification

• Operational resilience and scalability

Data engineering is a colossal and highly specialised industry that represents a CAGR of 17.6%). Given the sheer variety of tech stacks on show, generalists are struggling to compete in today’s talent market.

As a result, we’re seeing decision-makers struggle to pinpoint the right data engineers, even when they’re aware that access to top talent is a key differentiator in a fast-moving market.

Hyper Growth

Between the recent influx of applications, the expansion of role responsibilities, and uncertain macroeconomic conditions, it’s never been so important to field a robust and adaptable talent strategy.

Despite appearing like a saturated market in some areas, it’s worth bearing in mind that data engineering is one of the fastest-growing talent markets globally – the US Bureau of Labour Statistics expects the database administration and architects market (which includes data engineers) to grow by 8% between 2022 and 2032, which is faster than the average for all other occupations.

Demand for talent is still outstripping supply in critical growth areas, including blockchain, digital healthcare, and finance, underscored by the meteoric rise of AI. Whether you’re waiting for the LLM bubble to burst or you’re navigating the complexities of an AI-inspired transformation, data engineers are here to stay.

Modern AI is built on data. The world’s rate of data creation is accelerating. There is a golden opportunity for data engineers to help shape the future.

What’s Next?

The tools and techniques used in data engineering will keep changing. They already look completely different from what they did five years ago (hello cloud-native), a trend that’s likely to continue.

Alongside technical updates, regulatory pressures are set to shape the future of data engineering, not least of all the EU AI Act’s emphasis on data integrity and human oversight, especially in high-risk systems.

For many, this introduces a new layer of complexity into the hiring process – the need to target agile, security-minded learners who understand both the technical and ethical implications of their work.

If you’re struggling to find the right talent for your data engineering jobs, consider:

• Focusing on candidates who are both technically proficient and capable of positively contributing to your culture (culture-add over culture fit).

• Developing a strong understanding of data engineering fundamentals enables you to better align the recruitment process to the specific needs of your project.

• Building clear career pathways. It seems like every company has a different idea of data engineering. Cut through the noise and show your candidates you understand the complexity of the role.

• Broadening the talent pool. Backed by the Skilled Immigration Act, German companies are increasingly turning to foreign talent to close skill gaps. Adopting a diversity-led hiring strategy to search further afield can help you secure your candidates.

• Offer a customised remuneration package. Top data engineers know their value. You’ll need to work on your brand value proposition and develop targeted benefits (flexible working, parental leave packages, etc) to spark their interest.

Want more tips and insights? Hoping to secure the best strategy-aligned, culture-add data engineers on the market? Let’s talk: francis.alexander@trustinsoda.com.

​