Data Warehousing Concepts, Data governance and quality assurance practices, Building scalable and reliable data pipelines, Data Modeling Techniques and Methodologies, Data integration and transformation tools and frameworks, Database design principles

Pytest, Azure Databricks, Sql, Nosql, Numpy, Devops, Git, Pandas, Azure Functions, Flask, Integration Testing, Microsoft Azure, FastAPI, Rest Apis, Python, Backend Services, Data Pipelines, ETL Processes, CI/CD Pipelines, Scikit-learn, Timeseries Data Analytics, Data Processing

Github, Unix, Git, Linux Shell Scripting, Pl Sql, Python, Sql, Aws S3, ETL processes, Oracle databases, Control-M

Java, Data Security, PostgreSQL, SQL Server, Apache Spark, Data Governance, Sql, Databricks, Data Modelling, Testing Frameworks, Python, AWS, Airflow, Batch and streaming data pipelines, Monitoring and observability tools, Data quality and validation, dbt, CI CD pipelines

Rest Apis, Pytest, Numpy, Pandas, Azure Functions, Azure Databricks, Integration Testing, FastAPI, Python, Git, Flask, Microsoft Azure, Scikit-learn, Data Pipelines, ETL processes