I started my career in data and have stayed in it ever since, going from automating spreadsheets to building data platforms in the cloud.
Marisa (December 2017 – January 2018): in my first internship, I watched analysts and interns put together the same Excel reports by hand every single day. After a talk with my boss, I spent the rest of my summer internship automating them with VBA.
Medcel (January – June 2019): besides more VBA automation, I helped the data analyst with SQL queries, Tableau dashboards and Python scripts. I also built a web scraper with Selenium to find everyone who passed medical residency exams and which of them had been our customers, in time for a board meeting two weeks later.
Mobly (July – November 2019): in a bigger team, I got to know the work of a data engineer up close, along with tools like Apache Airflow and Pentaho and, for the first time, the cloud, on AWS. That’s when I decided to move fully into data engineering.
Revelo (December 2019 – February 2021): I joined as a “senior intern” and was soon promoted to data engineer, the only one in the company. My main project took the analysts’ queries off the production database: an Airflow instance on GCP copied a replica of the Postgres database on AWS to Google Cloud Storage and loaded it into BigQuery, all built from scratch. At the end of 2020, I also took on SRE duties, automating my projects with GitHub Actions and adding observability with Prometheus and Grafana.
InfoPrice (from March 2021): in my first job after graduating, I joined a data engineering team whose data was, for the first time, the company’s main product instead of the back office. There I worked on one of the projects I’m proudest of: cutting the cost of the Spark jobs on AWS EMR by moving their machines from On-Demand to Spot instances.