Containers, Typescript, Python, Testing, Apis, Aws Services, Debugging, Integrations, MLops, Distributed Systems, Prompt engineering, Software design principles, Performance optimization, AI technologies, Workflow orchestration, Infrastructure as code, Observability, Machine learning services, Git-based CI/CD, Automated quality practices, Intelligent automation, Generative AI, Cloud platforms, Streaming technologies, Data ingestion, Retrieval-augmented generation, Secure development, LLM integrations, CI/CD practices

data vault , Performance Tuning, Apache Spark, Kafka, Data Modeling, Data Warehousing, Sql, Dimensional Modeling, Kinesis, Query Optimization, Python, Apache Iceberg, Airflow, CDC-based data ingestion, Flink, Batch streaming, Workflow orchestration, Large-scale data processing, Delta Lake, Apache Hudi

data engineering , data vault , Apache Spark, Kafka, Sql, Git, Kinesis, Data Warehousing, Python, Apache Iceberg, Airflow, Infrastructure as Code, Flink, Delta Lake, Apache Hudi

data discovery , Google Cloud Platform, Kafka, Data Modeling, Data Lineage, Sql, Metadata Management, Python, Data lakehouse principles, Parquet, cdc, SCDs, Streaming architectures, Google BigQuery, Dimensional models, Pub Sub, AI ML use cases, Google Cloud Storage, Data pipelines, Data versioning

Github, Apache Flink, Csv, PostgreSQL, Apache Spark, Edi, Json, Redis, Typescript, Docker, MySQL, Xml, MongoDB, Restful Apis, Python, Airflow, Go

Java, Python, Spark, Kafka, Trino, Iceberg

snowflake , Sqlalchemy, FastAPI, Python, Kubernetes, Azure DevOps, Confluent Kafka, Pydantic, CI/CD implementations, DevOps practices, Microsoft Azure services, Cloud-native technologies

React, Terraform, Docker, Kubernetes, Python, AWS, Data Pipelines, Go, AI-assisted tooling, Analytics Systems

Scala, Java, Deep Learning, Machine Learning, C, Javascript, Apache Spark, Big Data, Python