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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Google Data Specialist - **Company:** Accenture - **Location:** Denver, CO, United States - **Experience:** Experienced - **Salary:** $59,100.0 - $196,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Architectural Patterns, BigQuery, Cloud Engineering, Cloud Storage, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, DevOps, Data Flow Control, Identity and Access Management, Python (Programming Language), Machine Learning, Meta-Data Management, Performance Tuning, Query Optimization, Cloudera, Security Support Provider Interface, SQL Databases, Google Cloud, Data Ingestion, Google Data Studio, Large Language Models, Prompt Engineering, Generative AI, Git, Data Lineage, Data Analytics, Machine Learning Operations, Virtual Agents, Looker Analytics, Data Pipelines - **Published:** June 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=fadb2697e71d81e5 ## About the Role Do you have experience in SQL?, Do you have a Associate's degree?, * 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 Bonus points if you have * 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. ## Description A hands-on Specialist 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. The Work (What You Will Do) As a GCP Data Specialist, you will help deliver data modernization, analytics, and AI solutions on GCP. You will support architecture design, build data pipelines and models, perform analysis, and contribute to technical implementations under guidance from senior team members. 1. 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. 2. 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. 3. 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. 4. 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. 5. 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. 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