Senior GCP Cloud Data Engineer & GenAI

Polly Hamilton Barnes
Dallas, TX, United States
2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
2 years minimum
Compensation
$150,000.0
Working hours
Regular working hours

Tech stack

Airflow Amazon Web Services BigQuery Cloud Database Cloud Engineering Cloud Storage Databases Data Control Information Engineering Data Governance Data Migration Data Systems
+30 more
Data Warehousing DevOps Graph Database Design of User Interfaces Apache Hadoop Hadoop Distributed File System Apache Hive Python (Programming Language) Node.Js NoSQL SQL Databases Data Streaming Web Applications Parquet Google Cloud Azure Data Factory ReactJS Apache Spark Git Pyspark Kubernetes Apache Flink Data Analytics Apache Kafka Spark Streaming Data Management Data Lakehouse Data Pipelines Docker Jenkins

Requirements

Must Haves: Cloud Engineer, GCP, LangChain or LangGraph

  • 5+ years of experience in data engineering including hands-on experience working with Hadoop and Google Cloud data solutions: creating/supporting Spark based processing, Kafka streaming, in a highly collaborative team
  • 2+ years of hands-on experience developing data flows using Kafka, Flink, and Spark streaming
  • 3+ years of experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Apache Kafka, Airflow, and SQL, GPC Cloud Storage, BigQuery, Data Proc, Cloud Composer
  • 2+ years working with NoSQL databases such as columnar databases, graph databases, document databases, KV stores, and associated data formats
  • Public cloud certifications such as GCP Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics
  • Proven skills with data migration from on-prem to a cloud native environment
  • Proven experience working with the Hadoop ecosystem capabilities such as Hive, HDFS, Parquet, Iceberg, and Delta Tables
  • Deep understanding of data warehouse, data cloud architecture, building data pipelines, and orchestration
  • Design and implementation of highly scalable and modular data pipelines with built-in data controls for automating data governance
  • Familiarity of GenAI frameworks such as Langchain and Langraph to develop agent-based data capabilities
  • Dev Ops and CI/CD deployments including Git, Jenkins, Docker, and Kubernetes
  • Web based UI development using React and Node JS is a plus

Benefits & conditions

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