I started developing databases in 2007. I work with databases and ETL tools every day. I work with my clients to determine and implement the best solutions considering all cost/effort/availability/technical tradeoffs for their problems. I commonly introduce or apply apply industry best practices to break down and solve problems; One of my preferred frameworks is the Kimball methodology.
My first and only language is English.
I have extensive experience with data systems in four core areas: Analysis, Warehousing, ETL, and Infrastructure.
For Analysis, my tool of choice is usually Tableau. If it’s a problem Tableau does not address, then I usually use Alteryx. If the problem is ML oriented, AWS Sagemaker usually gets the work if it’s not a use case that R covers inside Alteryx. I use Tableau 3-5 times a week since 2014. I can accommodate other platforms or custom internal platforms as well.
For Warehousing, I’ve built many data lakes using S3, Athena/Presto, EMR, Spark, Redshift, Snowflake and other tools/ecosystems. I also do database management type work with MySQL, Postgres, and the Hive Metastore. I have experience using metadata management systems, and designing workflows for using them. I’ve also created highly normalized databases with specific data models, and others with very specific parameters on access capability (high throughput, OLAP, OLTP, high concurrency, etc… )
For ETL, I have used Alteryx, AWS Glue, Spark, Talend, Pentaho, EMR and custom scripts. Each has different uses based on the technical capabilities and licensing. I’ve written specs on how the loading process and integration with other services works. For a large user base, there is usually a lot of time spent creating clear patterns and communicating them to all users, as opposed to time implementing the chosen tools. I am a Databricks Certified Developer: Apache Spark™ 2.X. Databricks is the company started by the initial developers of Apache Spark, which is the technology AWS Glue Jobs uses under the hood. I have used Spark on EMR, Databricks, and locally. I prefer Databricks in most big data production oriented cases.
For Infrastructure, I prefer using Amazon Web Services (AWS). I have 6 AWS Certifications. I work with AWS products every day and have used over 60% of their services in production environments.
Some of my favorite data tools are: Tableau, Alteryx, Spark (EMR, Glue, Databricks), DataGrip, Presto (Athena), Snowflake and any Amazon Web Services tool/service S3, RDS/Aurora, MySQL and Postgres, Redshift Spectrum. I also use Microsoft Excel.
I have these third party certifications:
- Alteryx Advanced Certified
- Amazon Web Services (AWS) Certified Solutions Architect - Professional
- Amazon Web Services (AWS) Certified Big Data - Specialty
- Amazon Web Services (AWS) Certified Advanced Networking - Specialty
- Amazon Web Services (AWS) Certified Machine Learning - Specialty
- Databricks Certified Developer: Apache Spark™ 2.X
- Tableau Desktop Qualified Associate
My first and only language is English.
I have extensive experience with data systems in four core areas: Analysis, Warehousing, ETL, and Infrastructure.
For Analysis, my tool of choice is usually Tableau. If it’s a problem Tableau does not address, then I usually use Alteryx. If the problem is ML oriented, AWS Sagemaker usually gets the work if it’s not a use case that R covers inside Alteryx. I use Tableau 3-5 times a week since 2014. I can accommodate other platforms or custom internal platforms as well.
For Warehousing, I’ve built many data lakes using S3, Athena/Presto, EMR, Spark, Redshift, Snowflake and other tools/ecosystems. I also do database management type work with MySQL, Postgres, and the Hive Metastore. I have experience using metadata management systems, and designing workflows for using them. I’ve also created highly normalized databases with specific data models, and others with very specific parameters on access capability (high throughput, OLAP, OLTP, high concurrency, etc… )
For ETL, I have used Alteryx, AWS Glue, Spark, Talend, Pentaho, EMR and custom scripts. Each has different uses based on the technical capabilities and licensing. I’ve written specs on how the loading process and integration with other services works. For a large user base, there is usually a lot of time spent creating clear patterns and communicating them to all users, as opposed to time implementing the chosen tools. I am a Databricks Certified Developer: Apache Spark™ 2.X. Databricks is the company started by the initial developers of Apache Spark, which is the technology AWS Glue Jobs uses under the hood. I have used Spark on EMR, Databricks, and locally. I prefer Databricks in most big data production oriented cases.
For Infrastructure, I prefer using Amazon Web Services (AWS). I have 6 AWS Certifications. I work with AWS products every day and have used over 60% of their services in production environments.
Some of my favorite data tools are: Tableau, Alteryx, Spark (EMR, Glue, Databricks), DataGrip, Presto (Athena), Snowflake and any Amazon Web Services tool/service S3, RDS/Aurora, MySQL and Postgres, Redshift Spectrum. I also use Microsoft Excel.
I have these third party certifications:
- Alteryx Advanced Certified
- Amazon Web Services (AWS) Certified Solutions Architect - Professional
- Amazon Web Services (AWS) Certified Big Data - Specialty
- Amazon Web Services (AWS) Certified Advanced Networking - Specialty
- Amazon Web Services (AWS) Certified Machine Learning - Specialty
- Databricks Certified Developer: Apache Spark™ 2.X
- Tableau Desktop Qualified Associate