Google Senior Data Engineer

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 Big Query, Looker, Vertex AI, Gemini Foundation Models, and Gemini Enterprise.

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.

• Hands-On Technical Delivery
• Build data pipelines, ETL/ELT processes, and integrations using GCP services such as:
  Big Query, Dataflow, Dataproc, Pub/Sub, Cloud Storage
• Assist with data modeling, performance tuning, and query optimization in Big Query.
• Implement data ingestion patterns for batch and streaming data sources.
• Support development of dashboards and analytics products using Looker or Looker Studio.
• 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-augmented generation (RAG) experimentation.
• Contribute to model testing, validation, and documentation.
• Requirements Gathering & Client Collaboration
• Participate in client workshops to understand data needs, use cases, and technical requirements.
• Help translate functional requirements into technical tasks and implementation plans.
• Communicate progress, blockers, and insights to project leads and client stakeholders.
• Data Governance, Quality & Security Support
• Implement metadata management, data quality checks, and lineage tracking using GCP tools (Dataplex, IAM).
• Follow best practices for security, identity management, and compliance.
• Support operational processes for data validation, testing, and monitoring.
• Continuous Learning & Team Support
• Learn and apply GCP Data & AI best practices across architectural patterns, engineering standards, and AI frameworks.
• Collaborate closely with senior data engineers, ML engineers, and architects.
• Contribute to internal accelerators, documentation, and reusable components.
• Stay current with GCP releases, Gemini model updates, and modern engineering practices.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

• Minimum of 5 years of hands‑on experience in Data Engineering, Data Analytics, ML Engineering, or related fields.
• Minimum of 4 years of practical experience with Google Cloud Platform.
• Minimum of 5 years of experience with SQL, data modeling, and building data pipelines.
• Minimum of 3 years of experience with Python or AI or GenAI tools (Vertex AI preferred).
• Bachelor’s degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

• Experience with GCP services such as Big Query, Dataflow, Pub/Sub, Dataproc, Cloud Storage, and Looker.
• Exposure to AI/ML development or experimentation with Vertex AI, Gemini models, embeddings, or RAG patterns.
• Hands‑on experience with CI/CD, Git, or cloud‑native engineering practices.
• Google Cloud certifications (Associate Cloud Engineer or Professional Data…