Azure Data Engineer
Current•Performed all phases of software engineering including requirements analysis, application design, and code development & testing.•Developed and maintained end-to-end operations of ETL data pipeline and worked with large data sets in azure data factory.•Increased the efficiency of data fetching by using queries for optimizing and indexing.•Wrote SQL queries using programs such as DDL, DML and indexes, triggers, views, stored procedures, functions and packages.•Worked on Azure Data Factory to integrate data of both on-prem (MYSQL, Cassandra) and cloud (Blob storage, Azure SQL DB) and applied transformations to load back to snowflake. •Deployed Data Factory for creating data pipelines to orchestrate the data into SQL database.•Developed custom activities using Azure Functions, Azure Databricks, and PowerShell scripts to perform data transformations, data cleaning, and data validation.•Working on Snowflake modelling using data warehousing techniques, data cleansing,Slowly Changing Dimension phenomenon, surrogate key assignment and change data capture.•Analytical approach to problem-solving; ability to use technology to solve business problems using Azure data factory, data lake and azure synapse.•Developed ELT/ETL pipelines to move data to and from Snowflake data store using combination of Python and Snowflake Snow SQL•Developing ETL transformations and validation using Spark-SQL/Spark Data Frames with Azure data bricks and Azure Data Factor•Developed and optimized code for Azure Functions to extract, transform, and load data from various sources, such as databases, APIs, and file systems.•Designed, built, and maintained data integration programs in a Hadoop and RDBMS •Processed HDFS data and created external tables using Hive and developed scripts to ingest and repair tables that can be reused across the project •Collaborated with DevOps engineers to developed automated CI/CD and test-driven development pipeline using azure as per the client requirement.