GCP Data Engineer

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profile Job Location:

Charlotte - USA

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Job Summary

The interview WILL be onsite in Charlotte or Hartford but then fully remote!

Required Skills & Experience

  • 8 years of experience across data engineering utilizing data solutions SQL and NoSQL Snowflake ELT/ETL tools CICD Bigdata GCP Python/Spark Datamesh Datalake Data Fabric
  • 1 year of hands-on experience supporting Gen AI initiatives in a data environment ideally from insurance background
  • Experience building out within ideally a GCP public cloud environment but could be AWS/Azure
  • Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow

Nice to Have Skills & Experience

  • AI certifications
  • GCP/Azure/AWS certifications
  • Experience in Property & Casualty or Employee Benefits industry
  • Knowledge of natural language processing (NLP) and computer vision technologies

Job Description

  • Responsible for implementing data pipelines that bring together structured semi-structured and unstructured data to support AI and Agentic solutions - includes pre-processing with extraction chunking embedding and grounding strategies to get the data ready
  • Develop GCP driven systems to improve data capabilities ensuring compliance with industry best practices for insurance-specific data use cases and challenges
  • Develop data domains and data products for various consumption archetypes including Reporting Data Science AI/ML Analytics etc.
  • Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the GCP environment.

The interview WILL be onsite in Charlotte or Hartford but then fully remote! Required Skills & Experience 8 years of experience across data engineering utilizing data solutions SQL and NoSQL Snowflake ELT/ETL tools CICD Bigdata GCP Python/Spark Datamesh Datalak...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala