Focusing on next generation AI Assistance across the products:

• [2026] Assistant is now "Genie code", contributed across all the surfaces https://www.databricks.com/blog/introducing-genie-code

• [2025] Created the first true Databricks Assistant Agent: Data Science Agent. Scaling framework to create Data Engineer Agent, Dashboard Agent...

• [2024] Improving AI suggestions quality (context fetching/re-ranking, citations...) and Assistants ( SDK, Query Optimization...)

• [2024] GA-ed first Co Pilot-style code completion to the Editors

• [2023] Added first AI Assistance to the Databricks products

• [2022] Unified the Editors across all the product and with Notebook

• [2021] Modernized the SQL Editor with a leading autocomplete and Monaco editor

https://www.databricks.com/blog/introducing-genie-code

https://www.databricks.com/blog/introducing-databricks-assistant-data-science-agent

https://www.databricks.com/blog/announcing-general-availability-databricks-assistant-and-ai-generated-comments

https://www.databricks.com/blog/introducing-databricks-assistant-autocomplete

https://www.databricks.com/blog/introducing-databricks-assistant

https://www.databricks.com/blog/2023/01/30/introducing-upgrades-databricks-notebooks-new-editor-python-formatting-and-more

Self service Data Warehousing in hybrid Clouds.

• Lead & co-creator of Hue, the open source Hadoop user interface: http://gethue.com. Evolved from a rudimentary tool to being used in thousands of companies by ten of thousands of users executing million of queries

• Cross company & components unification

• Lead of a very productive & fun team

• Focus on customer success, innovation, agility, data driven decisions and 100% delivery

• Full stack development, product strategy, vision, roadmap and prioritization with several major pivots

Cloud (Since 2017)

• Building Data Warehouse in Cloud platforms (AWS, GCP, Azure) with containerization via Kubernetes/Docker

• SQL Assistant for Cloudera's Data Warehouse service & Cloud platform

• Overall platform end user UX so that it becomes easier to use by non experts

• CICD, componentizations and designs to scale-up productivity

Data Warehouse (Since 2015)

• Tight integrations with Impala and Hive SQL Engines

• Built-in SQL tuning recommendations and troubleshooting with Cloudera Optimizer

• Data Catalog and search with Cloudera Navigator

Hadoop (Since 2012)

• Recreating Hue, the open source Hadoop user interface to make the platform easier to use

• Deep integration and understanding of the vast & evolving ecosystem (e.g. HDFS, YARN, Hive, Impala, Spark, Kafka, Solr, Oozie, HBase, Sentry, Pig, Flume...)

• End to end user experience, from install to basic ingest, querying and scheduling

Search team

Local Search

• Search improvements, Query Rewriting, Vespa (Lucene equivalent)

• Grid Log analysis of tens of metrics with Dashboard

• Log collection

Web Search

• Data processing with Hadoop. Content extraction and generation of new datasets for improving relevance and getting more insights.

Specialized in Pig:

• Query logs, session analysis, crawling, image recognition, language detection...

• Pig wrapper enabling transparent data-querying by non grid user.

• Contributed PigUnit, PigEditor.

Job Scheduler/Executer for the grid built from scratch (similar to Oozie and Azkaban):

• 500+ jobs / day, automatic retry of jobs / stateful (support restart) / consistent

• 30+ data pipelines, triggered between every 5 minutes or 6 months on multi clusters

• Web dashboard with Django / REST API

Infrastructure team

Worked on the Machine Database (which tracks the numerous Google servers and their parts) building:

• Web appplication for managing its metadata with Django

• Schema conversion in Python/Java. Schema visualization with SchemaSpy/prefuse

• Storing logs from C++ servers to BigTable through protocol buffers

Design and prototype of a tennis-booking website for a start-up during the summer.

Ajax technology through Google Web Tool Toolkit, MySQL, RPC Asynchronous Requests.