From Copilots to Autonomous Engineering Workflows

An EnablerMinds Webinar for Data & AI Engineers, Architects & Platform Teams

How AI-Assisted Development Is Reshaping Modern Data & AI Platforms

An EnablerMinds Webinar for Data & AI Engineers, Architects & Platform Teams

Modern Data & AI Engineering teams are under increasing pressure to deliver more pipelines,
AI solutions, faster insights, and higher quality — while platform complexity continues to grow.

At the same time, a new generation of AI-assisted engineering tools and autonomous coding agents
is transforming how software and data pipelines are developed.

In this webinar, EnablerMinds shares practical insights into how Agentic Coding is transforming Data & AI Engineering workflows across modern data and AI platforms such as Databricks, Microsoft Fabric, and Amazon Web Services.

Speakers

Hitesh Sahni

Co-Founder, EnablerMinds Germany | Enterprise Data Engineering & Platform Expert

Hitesh brings more than 15 years of experience designing and scaling enterprise data platforms across industries including logistics, automotive, banking, and life sciences.

He has led large-scale Data Engineering and Cloud initiatives for organizations including DHL, Volkswagen, Commerzbank, and Sanofi, with deep expertise in modern data platforms, cloud architectures, and engineering productivity.

Phanindra Parashar

Senior AI Engineer, EnablerMinds Germany

Phanindra specializes in building advanced AI solutions for complex, high-scale environments.

His experience spans autonomous driving, intelligent forecasting, and production-grade AI systems.

What You Will Learn

The Rise of Agentic Coding

How AI-assisted development is evolving
From copilots to autonomous engineering workflows
The Developer’s Role shifts

AI-Assisted Data & AI Engineering Workflows

AI-generated Spark, SQL, Python & dbt development
Accelerating data pipelines, AI workflows & feature engineering
Automated testing, documentation & code review
Faster implementation of data and AI solutions
Human + AI collaboration patterns

Productivity Gains & ROI Potential

Why Data & AI Engineering is one of the strongest adoption areas
Expected acceleration of engineering delivery cycles
Practical benchmarks and realistic expectations
Reduced engineering effort across data pipelines and AI solution delivery

Governance & Enterprise Considerations

Security & compliance implications
Human oversight & review workflows
Risks of uncontrolled AI-generated code
Best practices for enterprise adoption
Governance considerations for AI-generated data pipelines and AI applications

Live Demonstration

Practical examples of AI-assisted Data & AI Engineering workflows using:

Databricks Genie
dbt
PySpark & SQL pipeline generation
Testing & debugging workflows
AI-assisted Python development workflows

Who Should Attend?

This webinar is designed for:

Heads of Data Engineering
Heads of AI / AI Engineering
Data & AI Platform Leads
Data Engineers
AI Engineers / ML Engineers
Data Architects
Analytics Engineering Teams
Data Scientists building production solutions
CIO / CDO organizations
Engineering Managers
Modern Data & AI Platform teams

Particularly Relevant for Organizations Using:

Databricks
Microsoft Fabric
Amazon Web Services Data Services & AI Services
dbt
Spark-based Lakehouse platforms
AI Engineering platforms & modern Lakehouse ecosystems

About EnablerMinds

EnablerMinds is a specialized Data & AI consultancy focused on modern Data Platforms, AI Engineering, Lakehouse architectures, AI-driven data platforms, and enterprise AI adoption.

Our Expertise Includes:

Databricks
Microsoft Fabric
Amazon Web Services Data & AI Services
AI-assisted engineering workflows
Enterprise Data Platform modernization

The future Data & AI Engineer will spend less time writing repetitive code — and more time orchestrating intelligent engineering workflows.