Experience must have included Hands on experience in implementing, scheduling and maintaining ETL pipelines for onprem and to cloud AWS, Azure, GCP storages; Building large scale data batch jobs to be used and consumed by AIML teams for building ML models; Implementing Data Lake solutions to support analytics, reporting and data science teams using Big data technologies including Spark; Design, implement and maintain pipelines on different databases including RDBMS, NoSQL and distributed databases; Develop and build data and insights reporting tools on multi parallel processing data warehouses and databases using visualization tools including Power BI and Tableau; and Build databased APIs with low latency and high throughput.
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