Google Data Specialist

About the Role

Accenture is a 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 involves delivering solutions using Google Cloud's Data & AI platform, including BigQuery, Looker, Vertex AI, Gemini Foundation Models, and Gemini Enterprise.

The Work (What You Will Do)

Hands-On Technical Delivery

• Build data pipelines, ETL/ELT processes, and integrations using GCP services like: 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 (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 (0-100%) based 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.