Fernando Ferrer

Fernando Ferrer has worked on data projects for various clients:

As a senior data engineer for AddShoppers:

• Designed ETL pipeline to move over 100 million daily events from MongoDB to Postgres.
• Designed data warehouse using BigQuery.
• Refactored Python Django app to instrument events properly.

As a training consultant for SkillerWhale:

• Developed custom Postgres curriculum for corporate training, as well as test for different database courses.

As a MongoDB Administrator for AppviewX:

• Performed performance tuning of replica set.
• Created technical manuals for deployment and administration of a MongoDB Replicaset.

Immutable Data is an elastic data engineering and data science consulting firm. Fernando has managed several clients.

As a chief data officer for Sante Circle Health:

• Designed and architected secure data infrastructure on AWS.
• Managed a team of software engineers (three full-stack).
• Designed data warehouse on Redshift.
• Hired and mentored new talent.
• Designed and developed policies and procedures to be followed by the organization.
• Secured AWS infrastructure to ensure SOC Type 2 and HIPAA compliance.

As a senior data engineering consultant for SERMO:

• Built data warehouse in redshift to ingest over 1 billion records and reduce BI query time to 1 second or less.
• Built custom python ETL pipeline to move around 2 million data points per day from Postgres OLTP to Redshift to feed ML algorithm in order to mine physician posts and understand what there interest are.
• Administered SISENSE cluster and reporting platform to centralize BI reporting and reduce report loading to 5 seconds or less.
• Developed custom queries and SQL procedures for ad-hoc reporting.
• Redesigned data warehouse model to accommodate multi-dimensionality of data.
• Led the data team with eight engineers and two scientists).
• Maintained relationship with decision maker.
• Deployed ETL works across the organization.
• Trained engineers on Airflow deployment.

As a data engineering project lead for Kinduct Technologies:

• Administered JIRA board.
• Trained and developed in-house talent on project management and data engineering.
• Performed hiring interviews.
• Developed employee training and development map.
• Architected ETL pipeline using airflow, MySQL, Postgres, Redshift, and Snowflake.

As a director of technology and training for NobleProg:

• Developed training curriculum for courses in the data engineering and data science realm.
• Maintained client relationships.
• Delivered training for clients like L’Oreal Canada, Department of National Defense, Logitech East Asia, Government of Mexico, Bell Canada, TD Bank, and California Revenue Board.
• Awarded the Best Rated Training of 2018.

As a data engineering consultant for Androdon Capital:

• Developed a data pipeline using Python and google cloud as backend to move over 357 million records.
• Coded proprietary FX and stock trading models in C#.
• Processed over 3 million data points a day.

As a data consultant for the Government of Estonia:

• Developed a market report on the state of data scientist job market in North America.
• Introduced the idea of creating a conference focus on technology in North America. That idea matured to become what today is Latitude 44.

Hockeystick uses machine learning and data to help startups connect to funders.

• Built data warehouse data model.
• Developed infrastructure for DaaS offering using AWS stack.
• Cleaned ETL custom tool in Python to aggregate and clean data.
• Developed an operating budget for the data department.
• Created custom API using Python and Flask.
• Recruited engineering talent.
• Improved query times by 50% by altering the data model and improving indexes.
• Wrote Ruby on Rails controller to extract application data in real-time.

• Developed name matching algorithm to match web indexed data to physician database with an accuracy above 90% using Python and MySQL.
• Worked with data science team to collect application usage data to improve retention and usage.
• Developed ETL pipeline to ingest ICD9 and ICD10 codes from multiple sources in order to determine different key metrics of all medical procedures performed in USA.
• Created BI system hosting over 160 billion records.
• Developed career plan and compensation for the engineering department.
• Reduced query times by 66% by improving indexes and query caching.
• Reduced data ingestion times by 85% by moving on-premise infrastructure to AWS.
• Reduced cost of infrastructure by provisioning AWS reserved instances.
• Refactored front end app to use MongoDB.
• Developed ETL tool to move data from Hadoop EMR to MongoDB.
• Worked with data scientist to create a network of influence algorithm.
• Led technology audit prior to selling the business.
• Negotiated with counterparty during acquisition.