data engineering , Cloud Platforms (preferably AWS), Data Modeling, Data Warehousing, Data Analytics, Sql, Python, Modern Data Stack Tools, Data Pipelines

Metadata Management, Distributed Systems, Python, Data Transformation, Data Lineage, Pandas, Data Governance, FastAPI, Rest Apis, Apache Iceberg, microservices patterns, orchestration pipelines, LangGraph, AI Harness, Trino, Pydantic, data ingestion, observability, LangChain, Parquet, multi-agent frameworks, Generative AI, tracing, event-driven architectures, Monitoring, DuckDB, Agentic AI, LLM-based solutions, dbt, SDKs

Data Cleaning, Python, Sql, automated evaluation, information extraction, data extraction workflows, LLM workflows, Batch Processing, prompt engineering

Building data pipelines, Data Analysis

Prototyping, Pyspark, Data Modeling, Automation, Sql, Python, Data ingestion, ETL pipelines, AI-enabled data solutions

Query Optimization, Java, Performance Tuning, Scala, Data Integration, Python, Sql, data pipelines, data quality monitoring

Java, Servicenow, Scala, Sql, Apache Airflow, Python, Incident Management, Production Data Operations, Data lakes, Observability frameworks, Distributed data processing systems, Databricks job monitoring, Data quality controls, Validation frameworks, Performance optimization, Cloud-based data platforms

Java, Api Development, Sql, ELT, Database Technologies, Data Integration, Python, Etl, data pipelines, cloud platforms, analytics tools, data-processing

Data Transformation, Data Modelling, Etl Development, Scala, Apache Spark, Data Integration, Python, loading preparing and processing datasets, integrating Spark processing with Elasticsearch, Azure Data Engineering, Spark-based data processing, data ingestion

data engineering , Databricks, Sql, Apache Spark, Pyspark, Kafka, Cloud security, Data Governance, Python, Production pipelines, Cloud-scale analytics, Microsoft Fabric, Access Control, Delta Lake, Operational risk policies