Roles and Responsibilities:

8+ years of experience in creating Data Platform Solutions

5+ years of experience in implementing Data bricks, Data bricks Note book, Data Lakes, Data warehouse and Data Lake Architectures best practices for data storage, loading, retrieving data from data lakes.

3+ years of Azure Cloud Technologies building pipelines using Pyspark/Python

Must have good understanding of Azure Data Lakes and hands-on experience in implementing best practices in data storage, loading, retrieving data from data lakes.

Deep experience in Azure Platform and Azure Data Services

- Data Processing & Transformation using DataBricks, HDInsight, Azure Functions

- Data Staging & Storage using Data Lake Store, Synapse, Cosmos DB

- Data Ingestion using Event Hub

- Data Orchestration using Azure Data Factory

- Working on Azure Databricks

- Spark scripts to process the data loads to different layers

- Understanding of AI/ML Services, Data Modelling & Analytics

- Engineer and maintain a modern Cloud data pipeline for ETL/ELT

- Implement modern data solutions with Azure Data Factory, Data Lake, Data Bricks, SQL data warehouse, and Cosmos DB.

Azure Data Engineer Certification is preferable

Good to have –

-          Machine learning experience

-          Big Data knowledge

-          Snowflake or Big Query knowledge