Neo4j, Databricks, Python, MCP integration, pgvector, MCP prompt eval tooling, LLM cost governance, LLM orchestration, vector databases, RAG pipelines, graph stores

data engineering , BigQuery, Analytics Delivery, Jira, Sql, ML AI, Cloud Data Warehousing, Agile Delivery

snowflake , Machine Learning, Sql, Tensorflow, MLops, Pytorch, Netsuite, Spark, Databricks, Python, Salesforce, AI tools, scikit-learn, dbt, Fivetran

Google Cloud Platform (GCP), Hadoop Ecosystem, BigQuery, Scala, Apache Spark, Kafka, Dataproc, Data Modeling, ELT, Cloud Storage, DataFlow, Etl, Airflow, pipeline orchestration, Pub/Sub

data engineering , Google Cloud Platform, Digital Transformation, Cloud Migration, Data Quality, Data Warehousing, Microsoft Azure, Databricks, Data Governance, AWS, Etl, Data Lakes, Data Pipelines, Analytics, Advanced Analytics Platforms, Business Intelligence Reporting, ELT Frameworks

snowflake , Data Modeling, BigQuery, Kafka, Redshift, Sql, ELT, Spark, Python, Etl, AWS, Airflow, dbt, observability tooling

bedrock , containerization , Deep Learning, Nlp, Python, Orchestration, S3, Aws Services, Version Control, Git, Lambda, Docker, Kubernetes, GenAI, LLMs, vector stores, Classical ML, ML frameworks, EKS, SageMaker, Athena, RAG agentic architecture

, Identity Management, Agile Development, Data Warehousing, Oauth, Data Modelling, Cloud security, Software Engineering, Cloud Technologies, Sso, ETL processes, Customer 360 degree views, Master data management, Data technologies

Gcp, Azure, Python, Sql, AWS, DataOps, dbt, Data engineering best practices, CI/CD, Data pipelines

Python, Sql, ELT, Etl, Azure Synapse Analytics, Azure Data Factory, Devops, Git, Scala, Azure DevOps, Azure SQL Data Lake Storage