About This Role
Designing, implementing, and governing enterprise-scale data and AI platforms on cloud environments is the core of this contract role. The ideal candidate will have strong expertise in cloud-native data architectures, AI/ML platforms, data governance, and modern analytics ecosystems. This role will drive the design of scalable, secure, and resilient solutions that enable advanced analytics, Generative AI, and machine learning use cases.
Responsibilities
- Design and implement enterprise data architectures on Azure, AWS, or GCP
- Define end-to-end data strategy, including ingestion, storage, transformation, governance, and consumption
- Architect AI/ML and Generative AI platforms using cloud-native services
- Design scalable data lakes, lakehouses, data warehouses, and real-time data processing solutions
- Establish data governance, metadata management, security, privacy, and compliance frameworks
- Collaborate with business stakeholders, data scientists, engineers, and product teams to deliver AI-driven solutions
- Define data standards, architecture principles, and best practices
- Evaluate and recommend emerging technologies related to AI, cloud, and analytics
- Lead architecture reviews and ensure alignment with enterprise architecture standards
- Support implementation of MLOps, DataOps, and AI governance frameworks
Requirements
- Strong experience in Cloud Architecture, Data Engineering, and AI Platforms
- Expertise in Azure, AWS, or Google Cloud Platform
- Experience designing modern data architectures including:
- Data Lakes
- Lakehouses
- Data Warehouses
- Streaming Architectures
- Hands-on experience with:
- Databricks
- Snowflake
- Azure Synapse
- Azure Data Factory
- AWS Glue
- BigQuery
- Strong knowledge of AI/ML ecosystems and Generative AI technologies
- Experience with Large Language Models (LLMs), RAG architectures, Vector Databases, and AI Agents
- Proficiency in Python, SQL, and distributed data processing frameworks
- Knowledge of data security, governance, and regulatory compliance
- Excellent stakeholder management and leadership skills
Nice to have:
- Experience implementing enterprise GenAI solutions
- Knowledge of Azure OpenAI, Amazon Bedrock, Vertex AI, or similar services
- Experience with Kubernetes, Docker, and microservices architecture
- Familiarity with MLOps tools such as MLflow, Kubeflow, or Azure ML
