Google Data Specialist
About The Position
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. This role is for a hands-on Specialist with foundational experience in Data Engineering, Analytics, or Machine Learning, who is building deep expertise in Google Cloud Platform (GCP). The individual will apply technical skills, learn advanced Data & AI patterns, and support delivery teams in designing and implementing modern data and AI solutions. They will be comfortable working directly with clients, supporting senior architects, and contributing to end-to-end project execution.
Requirements
- 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.
- Minimum of 2 years of experience with SQL, data modeling, and building data pipelines.
- Minimum of 2 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 equivalent minimum 6-year work experience.
Nice To Haves
- 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.
Responsibilities
- 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.
- 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.
- 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.
- Support implementation of 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.
- 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.
Benefits
- medical
- dental
- vision
- life
- long-term disability coverage
- a 401(k) plan
- bonus opportunities
- paid holidays
- paid time off
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
