data warehouses , snowflake , Power Bi, Data Modeling, Data Lineage, Jira, Sql, Dimensional Modeling, Data Visualization, Python, AWS, ELT patterns, Semantic layers, Data Validation, Analytics engineering, Data automation, Project Management, Version-controlled analytics code

data engineering , Data Transformation, Power Bi, Data Modeling, Sql, ELT, Git, Microsoft Azure, Python, Azure DevOps, Etl, table maintenance, data quality checks, OneLake, data pipelines, schema validation, Spark notebooks, cloud data platforms, Microsoft Fabric, ADF pipelines, Lakehouse tables

Hive, Hadoop, Pyspark, Data Warehousing Concepts, Bash, Sparksql, Python, Sql, Big Data Technologies, Airflow, DataFrame

software design patterns , snowflake , Apache Airflow, Docker, Terraform, Python, Database Concepts, Unit Testing, Sql, Version Control, Test automation, Databricks, Apache Beam, Kubernetes, GCP Dataflow, Google BigQuery, Google Cloud Platform GCP, Pub Sub, Infrastructure as code, Data pipelines, GCP Cloud Run, ETL ELT processes, Cloud Logging Monitoring, Data processing frameworks Pandas, CI CD pipelines, Data visualization tools, GitLab CI CD

Hadoop, Scala, Pl Sql, Emr, Sparksql, Data Modeling, Ddl, Bodi, Informatica, SSIS, Sql, Hive, Odi, Datastage, Hiveql, Spark, Python, MDX, Warehousing, KornShell, ETL pipelines

data engineering , Python, Pyspark, Azure Databricks, Data Modeling, Kafka Stream

containerization , Github, Graphql, Database Development, Data Modeling, Docker, Restful Apis, Python, Index maintenance, Advanced SQL queries, Stored procedures, Query performance tuning, Data warehousing principles, WebSockets

Data Governance, Data Warehousing Concepts, ETL process design, data storage solutions, distributed computing environments, cloud-based data platforms, Microsoft Azure Databricks, security best practices, data pipeline architecture

snowflake , Etl, Sql, Databricks, ELT, Data Modeling, Data Governance, Devops, Pyspark, Data Warehousing, Python, Security, AI GenAI capabilities, performance optimization