Google Data Specialist

About the Role

Accenture is a premier Google Cloud partner focused on modernizing data ecosystems, building real-time analytics, and scaling AI. As part of Accenture Cloud First and the Accenture Google Business Group (AGBG), this role leverages Google Cloud's Data & AI platform.

The Work

As a GCP Data Specialist, you will help deliver data modernization, analytics, and AI solutions on GCP. Responsibilities include supporting architecture design, building data pipelines and models, performing analysis, and contributing to technical implementations under senior guidance.

Key Responsibilities

• 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.
• 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.
• 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.
• 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, varying from 0 to 100% depending on business need and client requirements.

Requirements & Tech Stack

• Minimum of 2 years of hands-on experience in Data Engineering, Data Analytics, ML Engineering, or related fields.
• Minimum of 2 years of practical experience with Google Cloud Platform (GCP).
• Minimum of 2 years of experience with SQL, data modeling, and building data pipelines.
• Minimum of 2 years of experience with Python or AI/GenAI tools (Vertex AI preferred).
• Bachelor's degree or equivalent (minimum 12 years' work experience). If Associate's Degree, must have equivalent minimum 6-year work experience.

Bonus Points

• Familiarity with GCP services such as BigQuery, 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 Engineer).
• Experience working in agile delivery environments.