Featured

How to Become a Data Engineer in 2026

Hosted by Aki Wijesundara, PhD

Mon, Jan 26, 2026

10:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

Invite your network

Go deeper with a course

Data Engineering Bootcamp & Certificate
Aki Wijesundara, PhD and Manu Jayawardana
View syllabus

What you'll learn

A realistic view of the data engineer role in 2026

Understand how the role is evolving with modern data platforms, AI, and analytics needs.

The core skills data engineers actually use

Learn which technical foundations, tools, and practices matter most on the job.

How data engineers work with product, analytics, and AI team

See how requirements turn into production data systems.

Where to focus when learning or reskilling

Prioritize skills that translate to real-world impact.

How to move from learning to production work

Understand what differentiates practice projects from production pipelines.

Why this topic matters

The data engineer role is often described as tool-specific or narrowly technical. In reality, it’s about building reliable data systems that support real products and decisions. This session focuses on what the role actually looks like in 2026, helping learners invest time in the skills that matter.

You'll learn from

Aki Wijesundara, PhD

AI Founder | Educator | Google AI Accelerator Alum

Aki Wijesundara is an AI leader with a PhD in Machine Learning and extensive experience mentoring startups at Google’s AI Accelerator. With a career spanning both research and applied AI, Aki has taught 5,000+ students worldwide how to design and deploy production-ready AI systems.

He has worked across cutting-edge areas of applied AI, from LangChain and RAG pipelines to observability and large-scale deployment. As a researcher and educator, Aki bridges the gap between theory and practice, making complex systems approachable and actionable for engineers, founders, and product leaders.

Aki is also a frequent speaker and advisor to organizations adopting AI, helping them transition from experimentation to production at scale.


Career highlights

  • Ex–Google AI Accelerator researcher focused on responsible AI and applied ML.
  • PhD in AI & Cognitive Systems with published research across top universities.
  • Former researcher with teams affiliated with MIT, University of Oxford, & King’s College London.
  • Co-founder of Snapdrum — delivered AI systems for finance, education, and healthcare.
  • Built and deployed AI product pipelines used by PMs, startups, and enterprise teams.
  • Instructor for multiple AI builder programs, helping 500+ professionals ship AI features fast.


Previous Students from

Google
Meta
OpenAI
NVIDIA
Amazon Web Services

Sign up to join this lesson

By continuing, you agree to Maven's Terms and Privacy Policy.