Spark, Sql, Autosys, Hadoop, Kafka, Abinitio, Hive, Data Warehouse, Kubernetes, Python, Neo4j, Docker, MongoDB, Google Cloud Platform, Google Big Query

S3, Metadata Management, Pyspark, Streaming, Python, AWS, Version Control, Testing, Scala, Sql, Gcp, Spark, Data Governance, Databricks, Azure, job scheduling workflows, storage formats, security access controls, data transformations, data compliance, large-scale data pipelines, ADLS, best practices, Delta Lake, distributed data processing, cloud-native data architecture

Gcp, Spark, Azure, Python, Sql, AWS, ClickHouse

data engineering , S3, Big Data Technologies, MLops, Docker, Cloud Services, Kubernetes, Python, Etl, Infrastructure as Code, EKS, Containerized application development, Glue, Athena

Python, LangChain LangGraph CrewAI, Testing and clean Git workflows, FastAPI or similar frameworks, API integrations REST webhooks, Prompt structure and output handling, Understanding of how RAG systems use data, LLM API integration OpenAI Anthropic, Basic BI analytics tools, Docker CI-CD, Exposure to vector databases pgvector Pinecone, AWS GCP experience, Strong SQL and database design, Airflow Prefect or pipeline orchestration

data engineering , Kubernetes, Big Data Technologies, S3, MLops, Etl, Cloud Services, Python, Docker, EKS, Athena, Infrastructure as Code, Glue, Containerized application development

S3, Github, Tableau, Data Modeling, Informatica, Sql Development, Unix Shell Scripting, Lambda, Database Design, Version Control Systems, Etl Tools, Python, Aws Services, Database Security, Power Bi, SQL Server, Git, data visualization tools, data quality controls, Oracle databases, Control-M, PL SQL development, Step Functions, T-SQL development, AI-assisted development, CI CD pipelines