Keith Castelino

About Keith Castelino

I build and maintain data infrastructure that enables users of data to answer business questions with it.My career thus far is a result of accumulated learning that began as a business student in college. An initial intent to work in academia took me to grad school in Economics. A desire to work with data first took me to a client services role at Mu Sigma, with a switch to a more hands on role with data later achieved by returning to grad school for an MS in Business Analytics at Seattle University.I started my tenure at PACCAR as an accidental data engineer. While my original plan was to work as a data scientist, the opportunity to build data infrastructure/platforms that supports end users of data seemed more appealing. I have spent the last few years building applications and processes that ingest, transform and serve data from a variety of sources into the PACCAR Parts cloud. As a lead data engineer, I have been leading the implementation of best practices intended to help build testable documented datasets for end users of data.Skills I have- Programming: Python, SQL- Data warehousing: Snowflake- Data integration: Qlik Replicate- Data transformation: dbt- Infrastructure as Code: Terraform, Schemachange- AWS services: Lambda, S3, IAM, Secrets Manager, Transfer Family, EventBridge- CI/CD: GitHub Actions- Data visualization: Tableau, Power BISkills I am looking to develop further- Containers: Docker- Orchestration: Airflow, Kubernetes- Shiny new toys: DuckDB, StreamlitA lot of what I have learned over the past 2-3 years has come from suggested content I have found here on LinkedIn, through reading books like Fundamentals of Data Engineering as well as participating at conferences (like Snowflake Summit). I have grown by adapting industry best practices to my work and sharing with those that I work with. I would be happy to connect with other fellow data professionals, to exchange notes and share some of what I have learned to support others in developing their skills.

Experience

1. Lead Data Engineer

   PACCAR Parts

   Jun 2022 — Present · Seattle, WA, US

   As a technical lead in a team of data engineers, I lead the implementation of best practices to be followed for building testable documented datasets.Achievements include- Centralized the maintenance of data transformations into a single dbt project, run using a single workflow on GitHub Actions, with a contributors guide and accompanying documentation helping fellow data engineers and data scientists manage data dependencies, increase test coverage and document knowledge about transformed datasets- Defined an upgraded security model for managing permissions to Snowflake data, and the path to migrating end users off the legacy RBAC implementation- Designed standard applications for loading data into Snowflake, unloading data from Snowflake and archiving data according to Type 2 SCD (upgrading v1 that I built a few years ago)- Rolled out a secure CI/CD process (based on GitHub\'s support for OIDC) for the entire Advanced Analytics team to follow for deploying data applications to AWS from respective GitHub repos, eliminating the need for self hosted runners, while ensuring least privileges available to AWS services from respective repositories

Education

• Seattle University

  Master of Science - MS, Business Analytics

  2018 — 2020

• St Joseph's College of Commerce

  Bachelor’s Degree, Business Administration and Management, General

  2008 — 2011

• University at Buffalo

  Master of Science (M.S.), Economics

  2011 — 2013

Skills

• Hadoop
• Analytical Skills
• Powerpoint
• Microsoft Excel
• Data Visualization
• Editing
• Databases
• Data Analysis
• Economics
• Microsoft Word
• Python
• Hive
• Microsoft Office
• Writing
• Financial Modeling
• Css
• Statistics
• Sas
• Oracle Sql Developer
• Postgresql
• Teradata Sql
• Business Intelligence
• Analysis
• Microsoft Sql Server
• Sql
• Analytics
• Tableau
• Statistical Modeling
• Powerbi
• Html
• R