Pl Sql, Microsoft Azure, Azure Databricks, Python, Sql, AI ML tools

Debugging, Pyspark, Data Warehousing, Sql, Data Analysis, Postgres SQL or similar RDBMS, Data modeling fundamentals, Performance optimization, Azure cloud ecosystem or equivalent cloud platforms, ETL pipelines

Azure, Sql, Etl, Power Bi, Ci

snowflake , Sql, ELT, Nosql, Docker, Gitlab, Databricks, Rest Apis, Kubernetes, Python, Azure DevOps, Etl, GitHub Actions, Microsoft Fabric

Apache Flink, Data Modelling, Scala, PostgreSQL, Apache Spark, Schema Design, Sql, Devops, Hive, Spark Streaming, Docker, FastAPI, Python, Kubernetes, Parquet, Apache Iceberg, data security standards, data architecture principles, AI concepts and tools, cloud data platforms, Podman, ETL tools and frameworks, data pipeline orchestration

data discovery , Metadata Management, Kafka, Slas, Data Modeling, Python, Data Lineage, Google Cloud Platform, Sql, Query Optimization, Data Quality, Clustering, cdc, data pipelines, observability practices, dimensional models, Google BigQuery, data versioning, Pub Sub, data lakehouse principles, streaming architectures, Parquet, SCDs, AI ML use cases, SLOs, partitioning, Google Cloud Storage

Power Bi, Pyspark, Pl Sql, Azure Databricks, Data Architecture, Power Query, Sql, Git, Azure Data Factory, Azure Data Lake, Dax, Oracle, Python, Azure DevOps, Azure Fabric