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SF Data Weekly - You're the top (5 or 10), an Exercise Decision Tree, and Career Advice

September 4 · Issue #153 · View online
SF Data Weekly
This week, in addition to highlighting a few interesting job opportunities, we’re including a couple of pieces on jobs and the interview process, including a set of fascinating interviews with Lyft data scientists, as well some experience-based interview tips for data engineers.
We’ve also got a lot of top n pieces, where n >= 5 and <= 10, and one surprisingly interesting piece about Iowa, made surprisingly interesting by using ArcGIS data visualizations. Stay healthy!

Our Pick
Go Out For Exercise Or Not? Let Data Science Decide | by Christopher Tao | Aug, 2020 | Towards Data Science
Data Pipelines
5 essential tips to build an ETL pipeline for a database hosted on Redshift using Apache Airflow | by Tran Nguyen | Aug, 2020 | Towards Data Science
Getting Started with Docker for Data Scientists | by Sara A. Metwalli | Aug, 2020 | Towards Data Science
Data Storage
Configure and optimize performance of Amazon Athena federation with Amazon Redshift | Amazon Web Services
Top 10 performance tuning techniques for Amazon Redshift | Amazon Web Services
Data Analysis
Top 5 SQL Analytic Functions Every Data Analyst Needs to Know | by Dario Radečić | Aug, 2020 | Towards Data Science
5 Jupyter Lab Hacks for a Better Life | by Meirav Ben Izhak | Aug, 2020 | Medium
Data Visualization
Adding layers of meaning to a travelogue
Best 5 tools for sketching analytics dashboards | by Nathalia Cardenas Mazo | Aug, 2020 | Medium
Data-driven Products
Tracing at Slack: Thinking in Causal Graphs - Slack Engineering
Data Engineering Jobs
Diving into Data Science. Meet Alya, Mike, and Troy! They are… | by Diversity in Science at Lyft | Aug, 2020 | Lyft Engineering
5 Data Science Interview Mistakes I’ve Made | by Matt Przybyla | Aug, 2020 | Towards Data Science
Here are our usual career picks:
Data Scientist - Trace Data
Intermix - build better data products with analytics into your data warehouse. Complete visibility into your data platform, who is touching your data, and how it’s being used.
Xplenty. - the leading data integration platform to bring all your data sources together. Trusted by companies like Gap, Samsung, Ikea, and Masterclass for their data pipelines.
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