Google Senior Data Engineer

Accenture; Cincinnati (OH); On-site; USD 110,000 - 160,000; Full time

Job summary

Accenture is seeking a hands-on GCP Senior Data Engineer to help deliver data modernization, analytics, and AI solutions on Google Cloud. You will build data pipelines, assist with data modeling and performance optimization, and support dashboards and AI model deployment under senior guidance.

You will work directly with clients, support architects, and contribute to end-to-end project delivery across BigQuery, Dataflow, Vertex AI and Gemini platforms.

Responsibilities

• Deliver data modernization, analytics and AI solutions on Google Cloud Platform (GCP).
• Build data pipelines and models using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage.
• Support development of dashboards and analytics products via Looker/Looker Studio.
• Assist in developing ML models and AI solutions using Vertex AI and Gemini platforms; help establish MLOps processes.

Job description

We Are

Accenture is a premier Google Cloud partner helping organizations modernize data ecosystems, build real-time analytics capabilities, and responsibly scale AI. As part of Accenture Cloud First and the Accenture Google Business Group (AGBG), we deliver solutions leveraging Google Cloud’s Data & AI platform—including BigQuery, Looker, Vertex AI, Gemini Foundation Models, and Gemini Enterprise.

You Are

A hands‑on Engineer with foundational experience in Data Engineering, Analytics, or Machine Learning—now building deep expertise in Google Cloud Platform (GCP). You are eager to apply technical skills, learn advanced Data & AI patterns, and support delivery teams in designing and implementing modern data and AI solutions.

You’re comfortable working directly with clients, supporting senior architects, and contributing to end‑to‑end project execution.

The Work (What You Will Do)

As a GCP Senior Data Engineer, you will help deliver data modernization, analytics, and AI solutions on GCP. You will support architecture design, build data pipelines and models, perform analysis, and contribute to technical implementations under guidance from senior team members.

1. Hands‑On Technical Delivery

• Build data pipelines, ETL/ELT processes, and integrations using GCP services such as: BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage
• Assist with data modeling, performance tuning, and query optimization in BigQuery.
• Implement data ingestion patterns for batch and streaming data sources.
• Support development of dashboards and analytics products using Looker or Looker Studio.

1. Support Agentic AI & ML Solution Development

• Assist in developing ML models and AI solutions using:Vertex AI, Gemini Foundation Models, Gemini Enterprise, Model APIs & Embeddings
• Implement ML pipelines and help establish MLOps processes (monitoring, retraining, deployment).
• Support prompt engineering, embeddings, and retrieval