Data Engineer

Roles and Responsibilities: Assembling large, complex sets of data that meet non-functional and functional business requirements. Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition. Working with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues Working with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues. Skills Required: Must have 3 or more years of experience in Data Engineering, ETL Development ETL DW Concepts - AWS (S3, Glue, Lamda, Athena, Step Function) Build data pipeline using Python, PySpark, SparkSQL Must have good understanding of MongoDB, DynamoDB, S3 Deliver business solution on Company's analytics platform through end-to-end implementation that includes data security, governance, cataloging, preparation, automated testing, and data quality metrics. Automate, optimize, migrate and enhance existing solutions. Adopt AWS data lake and data related services to implement end-to-end solution Perform data modeling, data analysis and providing insights using various tools.