Senior GCP Cloud Data Engineer & GenAI

Polly Hamilton Barnes

Dallas, TX, United States

16 days ago

Apply on www.careerjet.com

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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

Job source

www.careerjet.com

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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