Austin Levine
Partner / Gesellschafter, Consultant Business Intelligence, CaseWhen - Data & Business Intelligence Beratung
Berlin, Land Berlin, Germany, Deutschland
Über mich
I bring a decade of experience working with data in start-ups big and small across three continents. My expertise includes the “full stack” of data - from pipelining, to modelling, to reporting/dashboarding. From earlier in my career as an analyst, I learned data deeply from the business perspective, while my move to engineering has helped round out my technical approach. The perfect project allows me to solve tricky puzzles using SQL/python, while making meaningful connections with those I work with. I'm happiest when I'm able to learn from - and grow with - awesome people. When I'm not practicing my German (B2 in Bearbeitung!), you can find me daydreaming about the Mexican food back home in LA.
Werdegang
Berufserfahrung von Austin Levine
Bis heute 2 Jahre und 10 Monate, seit Sep. 2021
Consultant Business Intelligence
CaseWhen - Data & Business Intelligence BeratungWe help our customers go from: • Minimal to no reporting setup • Outdated, legacy setups based on Excel or Sheets • Patchwork, no-code setups that have become unmanageable • Aging setups that hold back their data's potential To: • Industry standard, modern data stack that scales • Fully automated reporting and dashboards • Validated data they can finally trust
11 Monate, Dez. 2020 - Okt. 2021
Senior Data & BI Engineer
Home HT
Modernized the entire Business Intelligence & analytics stack: Airflow, Snowflake, dbt, Fivetran, Metabase
Built the entire analytics architecture for the website, e-commerce shop, and order fulfilment lifecycle — from third party integrations (Airflow) to data modelling and validation (dbt), to dashboarding and discovery (Looker)
• Built complex Airflow jobs for ETL, third-party integrations, and data quality monitoring • Removed dependency on costly third-party data replication tool by building a more flexible version in-house • Provided SQL query optimization help for the Data team, cutting query costs by up to 99%
• A/B tested various in-app features by scoping event tracking requirements, designing experiments, building dashboards, automating readouts, and presenting learnings and recommendations to Product org • Created company and cross-functional squad KPIs through exploratory data analysis findings • Built machine learning models to predict user retention
2 Jahre und 4 Monate, März 2015 - Juni 2017
Product Analyst
Uber
• Owned reporting for global rider re-engagement campaigns; responsibilities included experiment design, KPI creation, automating readouts, presenting learnings • Built dashboards to monitor self-created squad KPIs and ongoing experiment results for Rider org
• Loaded, cleansed, and validated large sets of transactional data for U.S. Department of Justice FCPA investigations • Remotely managed a team of Associates in Deloitte’s U.S. India office