Data & AI Practitioner · Enterprise Architect

Turning complex enterprise data into scalable, real-world Lakehouse implementations.

Nicanor Medina

Director of Pre-Sales · SunnyData · Databricks Specialist

10+

YEARS OF EXPERIENCE

4

DATABRICKS CERTIFICATIONS

X

DATABRICKS PROJECTS SOLD

+5

NEW LOGOS FOR DATABRICKS

Nicanor Medina is a Data & AI practitioner with over 10 years of experience designing high-performance data architectures and enterprise solutions. As Director of Pre-Sales at SunnyData, he specializes in transforming complex business challenges into scalable systems using platforms like Databricks, AWS, and Snowflake.

His approach is grounded in execution: using data not as a static asset, but as a driver of real operational change.

ABOUT

  • Director of Pre-Sales | SunnyData

    Nicanor leads technical strategy and solution architecture for enterprise clients across the Americas. At SunnyData, he collaborates with organizations to design and implement Databricks-powered data platforms that drive innovation, efficiency, and business value.

    Key Responsibilities

    • Designing scalable Lakehouse architectures using Databricks.

    • Leading technical discovery sessions, demos, and proof-of-concepts.

    • Supporting enterprise data migrations from legacy systems to modern platforms.

    • Enabling organizations to adopt Data & AI best practices.

    • Driving strategic alignment between business objectives and technical solutions.

    • Promoting the adoption of Databricks across industries.

  • Nicanor is dedicated to fostering a collaborative and inclusive Data & AI community. Through mentorship, education, and technical advocacy, he actively supports professionals and organizations in their adoption of modern data technologies.

    Community Contributions

    • Sharing technical knowledge through articles and presentations.

    • Supporting teams and clients in adopting Databricks best practices.

    • Mentoring professionals entering the Data & AI field.

    • Promoting innovation and continuous learning.

    • Encouraging collaboration across the Databricks ecosystem.

    • Contributing to a culture of knowledge sharing and technical excellence.

  • As a practitioner deeply embedded in the Data & AI landscape, Nicanor contributes to the advancement of the Databricks ecosystem through hands-on implementations and technical leadership.

    Key Contributions

    • Architecting and delivering enterprise-grade Databricks solutions.

    • Implementing Lakehouse architectures for scalable analytics and AI.

    • Designing data governance frameworks using Unity Catalog.

    • Supporting data and AI initiatives powered by Apache Spark™ and Delta Lake.

    • Enabling machine learning workflows through MLflow.

    • Guiding organizations through legacy modernization and cloud migration.

    • Advocating for best practices in data engineering and platform architecture.

  • Nicanor’s work in data and AI is not just a profession, it’s a continuous pursuit of understanding how data can truly drive impact.

    What defines his approach is a deep curiosity for how systems behave at scale, how architectures evolve, and how technology decisions shape real business outcomes.

    He is not drawn to data for its complexity, but for its potential. To simplify, to clarify, and to unlock better ways of building.

    For Nicanor, working with Databricks is not about adopting a tool, it’s about engaging with an ecosystem that is actively redefining how data engineering, analytics, and AI come together.

    He is particularly motivated by the transition many organizations are going through today, moving from fragmented data stacks to unified platforms. Being part of that shift, and helping teams navigate it successfully, is a core driver behind his work.

Strategic Focus

Practitioner first.
Architect by design.

Nicanor's practice is grounded in a single conviction: technology should be invisible. What matters is whether systems work at scale, whether data flows correctly, and whether architecture maps to how organizations actually operate.

As Director of Pre-Sales at SunnyData, he translates complex enterprise requirements into concrete, production-ready blueprints — then ensures they ship. His focus is Financial Services: banking, fintech, and neobanks where data integrity and latency are non-negotiable.

He does not start with tools. He starts with the business problem, traces it to its structural root, and builds upward.

Deep diagnosis

Process-level analysis before any architecture decision

Invisible technology

Complexity absorbed by the system, not pushed to the user

Aligned architecture

Designs map directly to execution, not theoretical models

Structural impact

Identifies where data creates leverage, not just insight

Key Achievements

Holds Databricks certifications across Data Engineering, Lakehouse Fundamentals, Generative AI, and Unity Catalog Governance spanning the full platform surface.

Databricks Certified Data Engineer Associate

Databricks Generative AI Fundamentals

Databricks Lakehouse Fundamentals

Databricks Unity Catalog Governance

AWS Cloud Migration certified

ML Data Science & Machine Learning training

Case studies

Architectures that shipped.

Enterprise implementations led by Nicanor Medina at SunnyData — from initial pitch to production go-live.

FT
Farmatodo
Pharmacy chain · Latin America
The challenge
Post-Looker migration left Farmatodo with an underperforming Databricks AI/BI layer — slow queries, poor semantic structure, and limited self-service access for 100+ business users.
Architecture delivered
Databricks AI/BI Delta Lake Semantic layer Dashboard governance
60–70%
reduction in query times
400+
users on faster dashboards
100+
business users self-serve BI
DN
dichter & neira
Market research · AB InBev, Coca-Cola, Nestlé
The challenge
A LATAM research firm managing retail datasets for competing global brands needed strict data segregation, automated QA, and natural language access — on their existing Databricks platform.
Architecture delivered
Unity Catalog AI/BI Genie Data segregation Automated QA
2X
system efficiency improvement
65%
accuracy gain via automated QA
NL AI
Agent for retail dataset queries

Ecosystem engagement.

Participates in Databricks community conversations, shares practical implementation insights, and promotes adoption of best practices at enterprise scale.

Thought leadership

Published content.

Practical insights on Lakehouse architecture, platform migrations, and data engineering, written from the trenches, not from theory.

Featured Blogs

LET’S GET STARTED

Not a theory.
An operating system.