Ml, Microservices, Databricks, Azure, AWS, data, event-driven, serverless, cloud platforms, Ai, application architectures, Lakehouse, RAG, LLM orchestration, agentic architectures

Spark, Data Warehousing, Data Modeling, Sql, Python, Etl, Relational Database Design, reverse-ETL, Azure Technologies, batch data processing, micro-batch data processing

snowflake , S3, Pyspark, Kafka, Vpc, Lambda, Kinesis, Ec2, Docker, AWS, RDS, Cloudformation, Dynamodb, Redshift, Sql, Cloudwatch, Autoscaling, Data Lake, Etl, Aurora, SG, CloudTrail, API GW, CDC processing, Dms, Lake Formation, Glue, Nifi

Ml, Metadata Management, Distributed Systems, Data Modeling, Sql, Cloud Computing, Nosql, Data Architecture, Data Governance, AWS, Lakehouse Design, Ai, Palantir Foundry

snowflake , Data Modeling, Scala, Dimensional Modeling, Sql, Data Integration, ELT, Amazon Redshift, Spark, Data Warehousing, Python, AWS, Etl, Data Lakes

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

AWS AI Services, data integration methods and tools, Databricks Unified Data Analytics Platform, Snowflake Data Warehouse, database design principles, AI Data Solution Architecture, data modeling techniques

snowflake , Sqlalchemy, Cassandra, PostgreSQL, Pyspark, Kafka, Microservices, Numpy, Docker, Terraform, Distributed Systems, Python, Java, BigQuery, Scala, Redshift, REST, Pandas, Spark, MongoDB, FastAPI, Kubernetes, Airflow, Flink, GRPC, Dask, event-driven architectures, Dagster, data processing frameworks