Data Specialist
Location: Austin, TX, US
Industry: Business Consulting and Services
Work Setting: Hybrid

Are you passionate about modern data platforms, analytics, and emerging AI technologies? We are seeking a GCP Data Specialist to help design, build, and support cloud-based data, analytics, and AI solutions on Google Cloud Platform (GCP). This role is ideal for a hands-on engineer looking to deepen expertise in data engineering, machine learning, and Generative AI while collaborating with clients, architects, and delivery teams.
Position Summary
The GCP Data Specialist supports the delivery of data modernization, analytics, and AI initiatives by building data pipelines, implementing cloud-native solutions, supporting machine learning workloads, and helping clients unlock value from their data. The role combines technical delivery, client collaboration, data governance, and continuous learning within a modern cloud ecosystem.

Key Responsibilities
Data Engineering & Pipeline Development
Develop and maintain data pipelines, ETL/ELT processes, and integrations using GCP services.
Build batch and streaming ingestion solutions for structured and unstructured data.
Support enterprise data modernization and migration initiatives.
Design scalable data processing workflows to support reporting, analytics, and AI use cases.
Ensure data reliability, performance, and maintainability.
Google Cloud Platform Development
Work with core GCP services including:
BigQuery
Dataflow
Dataproc
Pub/Sub
Cloud Storage
Dataplex
IAM
Assist with cloud-native architecture implementation.
Support performance optimization and cost-efficient cloud solutions.
Implement secure and scalable data platforms.
Data Modeling & Analytics
Design and maintain logical and physical data models.
Optimize BigQuery queries and workloads for performance and scalability.
Support development of reporting and analytics assets.
Build and maintain datasets that enable business intelligence and analytics.
Assist with dashboard development using Looker and Looker Studio.
AI & Machine Learning Support
Support development of machine learning and Generative AI solutions.
Work with:
Vertex AI
Gemini Foundation Models
Gemini Enterprise
Embeddings
Model APIs
Assist in model deployment, monitoring, testing, and validation.
Participate in AI experimentation and proof-of-concept activities.
Contribute to AI solution documentation and implementation efforts.
Generative AI & RAG Development
Support prompt engineering initiatives.
Assist with Retrieval-Augmented Generation (RAG) implementations.
Work with embeddings and vector-based retrieval approaches.
Evaluate AI outputs and contribute to model improvement activities.
Participate in development of AI-powered business solutions.
Client Collaboration & Requirements Analysis
Participate in workshops and discovery sessions with clients.
Gather business and technical requirements.
Help translate functional requirements into implementation tasks.
Communicate project status, insights, blockers, and recommendations.
Collaborate with business stakeholders and technical teams throughout project delivery.
Data Governance, Quality & Security
Implement metadata management and data lineage solutions.
Support data governance initiatives using Dataplex and related tools.
Establish data quality validation and monitoring capabilities.
Follow security, compliance, and identity management best practices.
Assist with access control and governance activities using IAM.
Operational Support & Continuous Improvement
Support testing, validation, monitoring, and operational processes.
Assist with troubleshooting and issue resolution.
Contribute reusable frameworks, accelerators, and documentation.
Promote engineering best practices across delivery teams.
Identify opportunities for automation and process improvements.
Team Collaboration & Learning
Work closely with:
Senior Data Engineers
ML Engineers
Cloud Architects
Product Teams
Client Stakeholders
Continuously learn new GCP capabilities and AI technologies.
Stay current with Vertex AI, Gemini, and cloud platform enhancements.
Contribute to internal knowledge sharing and capability development.

Required Qualifications
Bachelor's degree or equivalent professional experience.
Minimum 2 years of experience in:
Data Engineering
Data Analytics
Machine Learning Engineering
Related technical fields
Minimum 2 years of hands-on Google Cloud Platform experience.
Minimum 2 years of experience with:
SQL
Data Modeling
Data Pipeline Development
Minimum 2 years of experience with:
Python
AI Tools
Generative AI Technologies
Vertex AI (preferred)
Strong analytical, communication, and problem-solving skills.
Technical Skills
Google Cloud Platform
BigQuery
Dataflow
Dataproc
Pub/Sub
Cloud Storage
Dataplex
IAM
Vertex AI
Data Engineering
ETL/ELT
Data Pipelines
Data Integration
Data Warehousing
Streaming Data Processing
Batch Processing
Programming & Analytics
SQL
Python
Data Modeling
Query Optimization
Data Analysis
Artificial Intelligence & Machine Learning
Vertex AI
Gemini Models
Generative AI
Prompt Engineering
Embeddings
Retrieval-Augmented Generation (RAG)
ML Pipelines
MLOps
Reporting & Visualization
Looker
Looker Studio
Dashboard Development
Business Intelligence
Data Visualization
Governance & Security
Data Governance
Data Quality
Data Lineage
Metadata Management
IAM
Cloud Security
Engineering Practices
Git
CI/CD
Agile Development
Cloud-Native Engineering
DevOps Fundamentals

Preferred Qualifications
Experience with:
BigQuery
Dataflow
Dataproc
Pub/Sub
Looker
Looker Studio
Exposure to:
Vertex AI
Gemini Models
RAG Architectures
Embeddings
Generative AI Solutions
Experience with Git and CI/CD pipelines.
Google Cloud certifications:
Associate Cloud Engineer
Professional Data Engineer
Experience working in Agile delivery environments.

Data Specialist

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