3 days ago
Pune, IndiaSenior
Responsibilities
- Architect and implement Snowflake-based AI/ML infrastructure for secure data access, feature preparation, model enablement, AI application integration, and production analytics.
- Write, review, and debug SQL, Python, scripts, and infrastructure-as-code for automation, monitoring, and deployment tooling.
- Configure and manage Snowflake warehouses, databases, schemas, secure access patterns, Snowpark workloads, Streamlit applications, data pipelines, and cloud storage integrations.
- Support deployment automation and CI/CD pipelines using Git, Terraform, dbt, Python, containers, and workflow orchestration tools.
- Deploy and operate data and feature pipelines, AI application integrations, and model-enablement components with attention to reliability, security, scalability, and cost efficiency.
- Monitor warehouse utilization, query performance, pipeline health, and integrations, and troubleshoot issues across compute, storage, access control, data movement, and application layers.
- Collaborate with data scientists, ML engineers, data engineers, platform engineers, and architects to integrate Snowflake-enabled AI solutions into enterprise systems.
- Document reusable patterns, configuration standards, and runbooks for Snowflake-based AI infrastructure.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- Minimum five years of experience is required for the project role; the qualifications also specify at least two years working with AI/ML infrastructure, data platforms, model deployment pipelines, or cloud/platform engineering solutions.
- At least two years of proficiency with programming or scripting languages such as Python, Java, C++, Bash, or PowerShell.
- Hands-on experience with Snowflake warehouses, databases, schemas, secure data sharing and access controls, Snowpark, Python/SQL workloads, and cloud storage integrations.
- Experience designing or operating scalable data pipelines, feature preparation workloads, AI application integrations, production analytics, or ML enablement workloads.
- Experience with CI/CD, infrastructure-as-code, containers, Kubernetes, workflow orchestration, operational monitoring, data observability, and cost/performance optimization.
- Strong understanding of AI/ML concepts and the compute, storage, networking, security, and deployment foundations needed to run AI workloads.
- Snowflake certification such as SnowPro Core, SnowPro Advanced Architect, or SnowPro Data Engineer is preferred.
- Preferred additional knowledge includes Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering, model enablement, data governance, data sharing controls, FinOps, incident management, and production support.
Categories
Data EngineeringDevOps
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.