data engineering , Spark, Databricks, Data ingestion strategies, Partitioning, ADLS, Resource Allocation, Incremental loads, Schema evolution, Spark optimization techniques, Caching

T-sql, Azure Functions, SQL Server, Microsoft Azure, Azure DevOps, GitHub Actions, Microsoft Entra ID, Service Bus, Azure App Services

Spark SQL, Storm, Flume, Kafka, Impala, Mapreduce, Pig, Apache Nifi, Rabbitmq, Hive, Gcp, Linux, Big Query, Hadoop v2, Airflow, HDFS, Data Proc, Cloud Composer, data fusion, dbt, Data Flow

snowflake , S3, Sql, Databricks, Azure Data Factory, AWS, Python, Gcp, Spark, Airflow, ADLS, Delta Lake, dbt

, Yarn, Java, Presto, Google Cloud, Kafka, AWS, Redis, Node.JS, Hive, Cassandra, Python, Azure, Golang, MongoDB, Spark, Airflow, HDFS, Map-Reduce, NoSQL databases, TiDB

Sql, Databricks, Pig, Pl Sql, Impala, RDBMS, Kinesis, Hadoop, Pyspark, AWS, Etl, Cassandra, Hive, Unix Shell Scripting, Python, Azure, Neo4j, Terraform, Apache Kafka, Git, MongoDB, Spark, CircleCI

Metadata Management, Data Modeling, Spark, Kafka, Python, Sql

? Advanced SQL (Complex Joins, Performance Tuning), ? Azure Data Lake Storage (ADLS), ? Data Governance & Data Lineage, ? Agile & RFC-Driven Environments, Databricks, Query Optimization, SQLDBM, Window Functions, ? Metadata Management, ? Power BI Semantic Models

data engineering , Aws Services, data models, Automation of recurring tasks, Data quality assessments, Cloud data warehouses, Data lakes, Master data management solutions