Key Skills: Azure Data Factory, Pyspark, TSQL, PLSQL, Exposure on other ETL Tools like SSIS, Databricks
Data Engineering
Create and maintain optimal data pipeline architecture
Design and develop Data Warehouse solutions
Assemble large, complex data sets that meet functional nonfunctional business requirements.
Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, redesigning infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide
variety of data sources using cloudbased technologies.
Migrate onprem processes from backoffice systems to the Cloud Azure or Salesforce.
Configure analytics tools that utilize the data pipeline to provide actionable insights into quality,
operational efficiency and other key metrics.
Work with stakeholders including the Product, Data, Finance, and Software Engineering teams to assist
with datarelated technical issues and support their data needs.
Keep data separated and secure Implement data tools for analytics, data scientist, and AI team members that assist them in building and optimizing current and new products. Work with data and analytics experts to strive for greater functionality in our data systems
