Picking Brains

What does a Data Engineer do?

I design and maintain data pipelines that turn raw data into reliable, accessible, and valuable insights to ensure stakeholders at my client can make meaningful decisions. My focus is on ensuring data is clean, connected, and ready for use, whether it’s powering dashboards, reports, or ad hoc analyses.

What excites you most about your role?

What excites me most is turning complex data into something truly useful. It’s not just about pipelines – it’s about delivering value and enabling smarter decisions. I enjoy solving tricky problems, collaborating with diverse teams, and staying sharp as tech evolves. Every case brings unique challenges, and building efficient, impactful systems is both intellectually rewarding and creatively fun. And on a personal level, I simply find coding fun.

Any specific technology you’re passionate about?

I’m passionate about Databricks. It’s flexible, user-friendly, and constantly evolving. They quickly roll out new features that genuinely improve workflows. Lately, I’ve been working a lot with their asset bundles to streamline deployments. I appreciate how it makes collaboration smoother and workflows more efficient. Whether you’re a data engineer, data scientist, or analyst, the platform meets you where you are.

What role does that technology play in a company’s data journey?

Databricks play a central role by connecting raw data with meaningful insights across the full data lifecycle – ingestion, transformation, analytics, and machine learning. It enables data engineers, scientists, and analysts to collaborate in one platform. With strong cloud integration and flexibility, it helps companies modernize and make smarter decisions faster.

How does a modern data platform foster data-driven organizations?

A modern data platform enables data-driven organizations by making data accessible, reliable and actionable across the business. Its biggest value is breaking down silos by unifying scattered data into one foundation for analysis and innovation. It also reduces technical complexity, so teams can focus on insights over infrastructure, empowering smarter decisions at every level.

Can you share a use case where it makes an impact?

In a recent project, we replaced a fragmented, unreliable setup with a unified data platform. It resolved issues like duplicated logic, lack of version control, and inconsistent reporting. By centralizing core logic, improving governance, and streamlining deployment with asset bundles, we’ve already seen better reliability, collaboration, and a stronger foundation for future growth.

Top advice for companies modernizing their data platform?

Focus on outcomes, not just reports or models. Prioritize trusted, clear business logic – if people can’t explain what a KPI means, it’s unlikely to drive value. Invest early in governance, scalability, and automation. Use tools like version control to ensure collaboration and stability. Involve users throughout the process and treat data as a product – built with usability, clarity, and long-term value in mind.

Filippa Peyron

Data Engineer