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Maintaining and improving several systems and pipelines that process large amounts of data through various types of ML models.
Occasionally making changes to these systems either for business or for regulatory purposes, testing the outcome of the changes thoroughly, and landing them in production
Supervising healthy operation of data pipelines required for reporting and experimentation and fixing issues as they arise
Creating data and report for regulatory purposes few times a year, making appropriate system changes to accommodate to changes in data ask and the scale of the data
Proactively testing existing systems and proposing improvements and bug fixes
Occasionally present findings and progress to the team
Desired Skillets : Must-haves :
Large-scale data processing aka data engineering
Parallel data processing
Python
Some form of SQL
Preferred :
Familiarity with ML systems
Experience of data analysis
What kind of prior work experience desired
Experience at Meta would be preferred
Experience at similar companies such as Google, Apple, Uber, Netflix etc.
Experience of building / maintaining large-data crunching systems