Data Warehousing Concepts, Databricks Unified Data Analytics Platform, data integration tools and techniques, cloud platforms and services related to data storage and processing, ETL processes, data governance and data quality best practices

data engineering , snowflake , Hadoop, PostgreSQL, Kafka, Data Integration, ELT, Nosql, Apache Airflow, Spark, Data Warehousing, Databricks, Data Governance, Oracle, Azure, Python, AWS, Etl, Flink, Teradata

data engineering , graph databases , object storage , AWS Glue, Data Modeling, Warehousing, column-family databases, data stores, key-value stores, IAM roles and permissions, non-relational databases, ETL pipelines

unstructured data , data engineering , Machine Learning, Data Science, Python, structured data, data pipelines, Data Processing, code reviews

Scala, Apache Spark, Kafka, Sql, Git, Gcp, Terraform, Databricks, Azure, Python, AWS, NoSQL databases, event-driven systems, data security principles, AI-assisted development tools, ML engineering, data governance frameworks

snowflake , Pyspark, Kafka, Sql, ELT, RDBMS, Spark, Databricks, Python, Etl, Data Transformation, Advanced Web-crawling, Building end-end Data Engineering pipelines, Scraping methods and tools, Kafka Streaming, AWS S3 Storage

snowflake , Hadoop, Power Bi, Scala, Kafka, Data Modeling, Sql, Apache Airflow, Git, Azure Data Factory, Docker, Spark, Python, data integration techniques, ETL processes, dbt