3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, automate, monitor, and optimize Snowflake-based AI/ML infrastructure.
- Configure Snowflake warehouses, databases, schemas, secure access patterns, Snowpark workloads, Streamlit applications, data pipelines, and cloud-storage integrations.
- Write, review, and debug SQL, Python, scripts, and infrastructure-as-code for automation, monitoring, and deployment tooling.
- Deploy and operate data and feature pipelines, AI application integrations, and model-enablement components.
- Support deployment automation and CI/CD pipelines using Git, Terraform, dbt, Python, containers, and workflow orchestration tools.
- Monitor warehouse utilization, query performance, pipeline health, integration health, reliability, security, scalability, and cost efficiency.
- Collaborate with data scientists, ML engineers, data engineers, platform engineers, and architects to integrate enterprise AI solutions.
- Document reusable infrastructure patterns, configuration standards, and operational runbooks.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- At least 5 years of experience is stated in the project role requirements; the qualifications section also specifies a minimum of 2 years in AI/ML infrastructure, data platforms, model deployment, or cloud/platform engineering.
- At least 2 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, and production analytics or ML enablement workloads.
- Experience with infrastructure-as-code, containers, Kubernetes, workflow orchestration, CI/CD pipelines, operational monitoring, data observability, and cost/performance optimization.
- Understanding of AI/ML concepts, compute, storage, networking, security, deployment foundations, MLOps/data-platform patterns, feature engineering, model input/output management, monitoring, and governance.
- Preferred qualifications include Snowflake certifications such as SnowPro Core, SnowPro Advanced Architect, or SnowPro Data Engineer; regulated-industry experience; and familiarity with Snowpark, Cortex/AI features, vector search, retrieval pipelines, FinOps, incident management, and production support.
Categories
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.