GCP Data & AI Specialist

Accenture; Culver City (CA); On-site; USD 70,350 - 196,000; Full time

Job summary

Accenture is seeking a GCP Data Specialist to help deliver data modernization, analytics, and AI solutions on Google Cloud. You will support architecture design, build data pipelines and models, perform analysis, and contribute to technical implementations under guidance from senior team members.

Travel may be required and you will collaborate with clients, data engineers, ML engineers, and architects to translate requirements into tasks and ensure secure, scalable data ecosystems.

Qualifications

• 2+ years hands-on experience in Data Engineering, Data Analytics, ML Engineering or related fields.
• 2+ years practical experience with Google Cloud Platform.
• 2+ years experience with SQL, data modeling and building data pipelines.
• 2+ years experience with Python or AI/GenAI tools (Vertex AI preferred).
• Bachelor's degree or equivalent; if Associate’s Degree, 6+ years work experience.

Responsibilities

• Deliver data modernization, analytics, and AI solutions on GCP.
• Support architecture design and build data pipelines and models.
• Assist in developing dashboards and analytics products using Looker or Looker Studio.
• Contribute to ML/AI solutions using Vertex AI, Gemini models, embeddings, and APIs.
• Implement ML pipelines and MLOps processes; participate in model testing and documentation.

Skills

Data Engineering

Data Analytics

ML Engineering

SQL

Python

Client collaboration

Education

Bachelor's degree or equivalent

Tools

BigQuery

Dataflow

Dataproc

Pub/Sub

Cloud Storage

Looker

Looker Studio

Vertex AI

Gemini Foundation Models

Gemini Enterprise

MLOps

CI/CD

Git

Job description

Accenture is seeking a GCP Data Specialist to help deliver data modernization, analytics, and AI solutions on Google Cloud. You will support architecture design, build data pipelines and models, perform analysis, and contribute to technical implementations under guidance from senior team members.

Travel may be required and you will collaborate with clients, data engineers, ML engineers, and architects to translate requirements into tasks and ensure secure, scalable data ecosystems.