sap applications , supply chain planning , Procurement, Inventory Control, Finance, Production Planning, Enterprise Resource Planning, Process Improvement, Supply Chain Analysis, Purchasing, Materials Management, Warehousing, Inventory Management, Data Analysis, Continuous Improvement Process, Lean Manufacturing, Material Requirements Planning, Supply Chain Management

data engineering , snowflake , Ml, Denodo, Power Bi, Pyspark, Azure Databricks, Automation, Devops, Azure Data Factory, FastAPI, Azure, Python, Azure DevOps, Azure App Services, Ai, Azure Key Vault, ADLSv2, YAML pipelines, Azure Cognitive Services

.NET, .Net Core, Linq, Web Api, Mq, CSS, Ibm Mq, Kafka, Rest Api, JQuery, Sql, React, Html5, Entity Framework, Mvc, GHCP, Agentic AI framework

containerization , Docker, Distributed Systems, API design, Kubernetes, Observability and monitoring solutions, DevOps practices, cloud-native architectures, Microservices architecture

.NET, .Net Core, Linq, Web Api, Mq, CSS, Ibm Mq, Kafka, Rest Api, JQuery, Sql, React, Html5, Entity Framework, Mvc, GHCP, Agentic AI framework

Cassandra, Pyspark, Apache Airflow, Nosql, Numpy, Docker, Azure Data Lake, Python, AWS, Spark SQL, Pycharm, Hadoop, Sql, Jenkins, Hive, Pandas, Azure, Kubernetes, DataFrames, GitHub Actions, Spark MLlib, HDFS, Jupyter, VSCode

Software Development Lifecycle, Gcp, Agile Methodologies, AWS, AI tools, performance engineering principles, platform scalability programs, distributed tracing, cloud infrastructure performance engineering, Hyperforce, CI CD pipelines, data fluency, observability

Github, Power Bi, Pl Sql, Tableau, Informatica, Sql, Unix Shell Scripting, Git, Python, Aws S3, Etl, data quality controls, Oracle databases, CI CD pipelines, Control-M

S3, Power Bi, PostgreSQL, Tableau, Data Modeling, Dimensional Modeling, Sql, ELT, Lambda, Amazon Redshift, MySQL, Data Warehousing, Python, AWS, Etl, Airflow, dbt, Glue

Sql, Kinesis, Kafka, AWS, Cloudformation, Python, Azure, Gcp, Terraform, Spark, dbt, Airflow, Prefect, Dagster, Pub Sub, DataOps practices