Google Data Specialist
About The Position
Accenture is hiring a hands-on Google Cloud data specialist to support data modernization, analytics, and AI solution delivery. The role contributes to architecture design, data pipelines and models, analysis, and technical implementations with guidance from senior team members. It involves working directly with clients, supporting senior architects, and contributing to end-to-end project execution across Accenture Cloud First and the Accenture Google Business Group. The specialist will build GCP-based data and AI solutions, help gather and translate client requirements, support governance, data quality, security, and operational processes, and collaborate with engineers and architects. The role emphasizes continued learning in Google Cloud Data & AI practices, including GCP services and Gemini updates. Travel may be required, varying from 0% to 100% based on business needs and client requirements.
Requirements
- At least 2 years of hands-on experience in data engineering, data analytics, ML engineering, or a related field.
- At least 2 years of practical experience with Google Cloud Platform.
- At least 2 years of experience with SQL, data modeling, and building data pipelines.
- At least 2 years of experience with Python or AI/GenAI tools; Vertex AI is preferred.
- Bachelor's degree or equivalent, defined as a minimum of 12 years of work experience. With an associate's degree, a minimum of 6 years of work experience is required.
Nice To Haves
- Familiarity with GCP services including 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 such as 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, and Cloud Storage.
- Assist with data modeling, performance tuning, and query optimization in BigQuery.
- Implement data ingestion patterns for batch and streaming sources.
- Support the development of dashboards and analytics products using Looker or Looker Studio.
- Assist in developing machine-learning models and AI solutions using Vertex AI, Gemini models, Gemini Enterprise, model APIs, and embeddings.
- Implement ML pipelines and help establish MLOps processes for monitoring, retraining, and deployment.
- Support prompt engineering, embeddings, and retrieval-augmented generation 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.
- Implement metadata management, data quality checks, and lineage tracking using GCP tools such as Dataplex and IAM.
- Follow security, identity management, and compliance best practices.
- Support data validation, testing, and monitoring operational processes.
- Learn and apply GCP Data & AI best practices, architectural patterns, engineering standards, and AI frameworks.
- Collaborate 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 insurance
- Dental insurance
- Vision insurance
- Life insurance
- Long-term disability coverage
- 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
