BigQuery, Google Cloud Platform, Pyspark, Spark, Dataproc, Sql, Airflow

Jenkins, Git, Aws Rds, PostgreSQL, AWS Glue, Python, Sql, Etl, Aws S3, AWS Batch

Data Governance, Data Warehousing Concepts, Data Architecture, Sql, Git, AWS, Snowflake architecture, ETL concepts, Data security practices, Snowflake SQL, Data modeling concepts, Data quality standards

snowflake , Github, Software Development, Data Transformation, PostgreSQL, Pyspark, Sql, React, Git, Pandas, Docker, FastAPI, NextJS, Python, LangChain, AI engineering, vector databases, Azure AI Agent Service, embedding-based retrieval, LangGraph, multi-agent workflows, agentic AI systems, LLM-powered applications

Devops, Hadoop, Scala, Spark, Data Warehousing, Sql, Python, Airflow, CI/CD pipelines

data engineering , snowflake , SQL Server, Redshift, Sql Development, Database Technologies, Databricks, Python, Data Stage, AWS, Etl, Data Warehousing technology, AI ML concepts, ELT frameworks, Data pipelines, ETL development using PowerCenter, DWH with data modeling

Git, SQL Server, Sql Development, Azure DevOps, Azure Data Lake Storage ADLS Gen2, ETL ELT pipelines, Synapse Analytics, Azure SQL Database, Azure Data Factory ADF

data engineering , Java, C#, Pyspark, Scala, Azure Databricks, Azure Synapse, Azure Data Factory, Python, Databricks Unified Data Analytics Platform, Microsoft Azure Data Services, Azure Data Lake Storage Gen 2, Scripting and programming languages, Data quality and consistency, Azure Blob Storage, Cloud-based data storage and processing solutions, Azure Fabric, ETL frameworks, Data Architecture Principles, Data pipelines, Monitoring and troubleshooting data workflows