Data Engineer

Themesoft Inc

Chandler, IN, United States

12 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Compensation

$83,200.0 - $93,600.0

Working hours

Regular working hours

Job source

www.indeed.com

Tech stack

Artificial Intelligence Airflow Big Data BigQuery Cloud Database Cloud Storage Information Engineering Python (Programming Language) Metadata Software Tools Data Streaming Google Cloud

+8 more

Apache Spark Pyspark Apache Flink Apache Kafka Spark Streaming Data Management Data Lakehouse Data Pipelines

Job description

Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest, transform, and distribute data for a variety of big data apps Leverage AI/Agentic frameworks to automate data management, governance, and data consumption capabilities - data pipelines, data quality, metadata, data compliance, etc. Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities 5 plus years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing 3 plus years of experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, BigQuery, Data Proc, Cloud Composer Hands-on experience developing data flows using Kafka, Flink, and Spark streaming, Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest, transform, and distribute data for a variety of big data apps Leverage AI/Agentic frameworks to automate data management, governance, and data consumption capabilities - data pipelines, data quality, metadata, data compliance, etc. Work within a matrix org. with principal engineers, product managers, and data engineers to roadmap, plan, and deliver key data capabilities based on priority

Requirements

GCP - 5 to 6 years. AI exposure - 6 months to a year Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities 5 plus years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing 3 plus years of experience with Data Lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, Big Query, Data Proc, Cloud Composer Hands-on experience developing data flows using Kafka, Flink, and Spark streaming