ZipRecruiter

Log In

1

Temporary Data Integration Developer Jobs in Chicago, IL

CoSourcing Partners

GCP Gemini AI Developer

Chicago, IL · On-site +1

The developer will work hands-on across data engineering, AI model orchestration, and API integration to create AI-driven business solutions that reduce manual effort, enhance decision-making, and ...

Pandata Group

Data Integration Consultant

Chicago, IL · On-site

As one of our Data Integration Consultants, you love a challenge and are eager to learn. You will ... Exposure to developer tools/ workflow (e.g. git/github, SSH) * Knowing how to get around a command ...

Purple Drive

Salesforce Data Cloud Developer

Chicago, IL · On-site

$57.25 - $75.75/hr

Chicago, IL / Remote Experience: 6-8 Years We are seeking an experienced Salesforce Data Cloud Developer with strong expertise in data integration, enterprise CRM architecture, and hands-on ...

Dentons

Integration Engineer

Chicago, IL

$107K - $144K/yr

Dentons US LLP is currently recruiting for a skilled and experienced Integration Engineer to design ... This role focuses on connecting disparate legal systems, ensuring reliable data flow between ...

Dentons

Integration Engineer

Chicago, IL · On-site

$110K - $140K/yr

Dentons US LLP is currently recruiting for a skilled and experienced Integration Engineer to design ... This role focuses on connecting disparate legal systems, ensuring reliable data flow between ...

next page

Showing results 1-20

All JobsTemporary Data Integration Developer JobsTemporary Data Integration Developer Jobs in Chicago, IL

Temporary Data Integration Developer information

See Chicago, IL salary details

$10

$53

$86

How much do temporary data integration developer jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for temporary data integration developer in Chicago, IL is $53.24, according to ZipRecruiter salary data. Most workers in this role earn between $44.81 and $59.90 per hour, depending on experience, location, and employer.
What are the most commonly searched types of Data Integration Developer jobs in Chicago, IL? The most popular types of Data Integration Developer jobs in Chicago, IL are:
Temporary Data Integration Developer jobs near you
GCP Gemini AI Developer

GCP Gemini AI Developer

CoSourcing Partners

Chicago, IL • On-site, Remote

Other

Posted 23 days ago

Job description

Job Title: GCP Gemini AI Developer (3-5 Years Experience)
Location: Remote / Hybrid - Chicago preferred
Employment Type: Contract / Full-Time
Reports To: GCP Technical Lead / AI Program Manager
Purpose
The GCP Gemini AI Developer will design, build, and deploy intelligent applications leveraging Google Cloud's Gemini models and Vertex AI platform. This role exists to operationalize advanced GenAI capabilities - including natural language understanding, multimodal reasoning, and generative automation - within scalable, secure, and production-ready cloud environments.
The developer will work hands-on across data engineering, AI model orchestration, and API integration to create AI-driven business solutions that reduce manual effort, enhance decision-making, and unlock measurable value from enterprise data.
Key Performance Outcomes (6-12 Months)OutcomeWhat Success Looks LikeMeasurement1. Gemini-Powered Solutions DeployedDesign, develop, and deploy at least two Gemini-based AI solutions (e.g., document summarization, chat agent, or data extraction automation) using Vertex AI + Gemini APIs.Delivered to production with >90% accuracy and <2s response time.2. Scalable Cloud ArchitectureBuild a modular AI microservices framework using Cloud Run / Cloud Functions with integrated authentication, logging, and monitoring.Reusable components adopted in at least 3 future use cases.3. RAG / Context-Aware WorkflowsImplement Retrieval-Augmented Generation (RAG) pipelines combining Gemini + BigQuery or vector databases for knowledge grounding.Demonstrated 25% reduction in hallucination or response variance.4. Cross-Team EnablementPartner with Data, Automation, and AppDev teams to integrate Gemini AI into existing business workflows (e.g., UiPath, Power Platform, or ServiceNow).Minimum of 2 successful integrations with documented ROI.5. Continuous OptimizationMonitor, retrain, and improve AI models via Vertex AI pipelines and Model Monitoring.Demonstrated 15% performance gain over baseline models.Core Responsibilities
  • Design and deploy Gemini 1.5 Pro/Flash integrations via Vertex AI and Generative AI Studio.
  • Build serverless APIs and backend services for AI workflows using Cloud Run, Functions, or App Engine.
  • Develop data ingestion and preprocessing pipelines using BigQuery, Dataform, and Pub/Sub.
  • Apply prompt engineering and parameter tuning to improve generative model accuracy.
  • Implement RAG pipelines leveraging Vertex Matching Engine or Pinecone.
  • Collaborate with automation and data teams to embed AI into existing business processes.
  • Maintain compliance with security, privacy, and model governance standards.

Technical Environment
Core Google Cloud Services
  • Vertex AI, Generative AI Studio, Gemini API
  • BigQuery, BigQuery ML, Dataform
  • Cloud Run, Cloud Functions, Cloud Storage
  • Pub/Sub, Secret Manager, IAM, Cloud Build

Programming Stack
  • Python or TypeScript (Google Cloud SDKs, google-generativeai, aiplatform)
  • FastAPI / Flask / Node.js
  • LangChain / LlamaIndex for orchestration
  • SQL, Pandas, and Jupyter for data prep

Complementary Tools
  • Terraform (IaC)
  • GitHub / GitLab CI/CD
  • Vertex AI Pipelines & Model Registry
  • Vector DB (Vertex Matching Engine, Pinecone, or Weaviate)

Ideal Profile
  • 3-5 years hands-on GCP development experience with AI/ML exposure
  • Strong working knowledge of Vertex AI, Gemini models, and RAG pipeline design
  • Demonstrated ability to move AI prototypes into production
  • Strong communicator, able to collaborate across automation, data, and cloud teams
  • Curious problem-solver passionate about applied AI innovation

Success Metrics
  • Speed to Delivery: End-to-end deployment within 8-10 weeks per use case
  • Model Effectiveness: >90% accuracy or relevance rating from business stakeholders
  • Scalability: Framework reused for 3 additional AI initiatives
  • Business Impact: 25%+ improvement in productivity or efficiency from deployed use cases

Apply