3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, automate, monitor, and optimize Snowflake-based AI/ML infrastructure and platform components.
- Write, review, and debug SQL, Python, scripts, and infrastructure-as-code for automation, monitoring, and deployment tooling.
- Configure 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.
- Monitor warehouse utilization, query performance, pipeline health, and integrations, and troubleshoot issues across compute, storage, access, data movement, and application layers.
- Collaborate with data scientists, ML engineers, data engineers, platform engineers, and architects to integrate enterprise AI solutions.
- Document reusable patterns, configuration standards, and operational runbooks for Snowflake AI infrastructure.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- Minimum five years of overall experience is required, including 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, and 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.
- Understanding of AI/ML concepts, compute, storage, networking, security, deployment foundations, MLOps/data-platform patterns, feature engineering, model input/output management, monitoring, and governance.
- Snowflake certification such as SnowPro Core, SnowPro Advanced Architect, SnowPro Data Engineer, or a related platform credential is preferred.
- Familiarity with Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering, data governance, FinOps, incident management, and production support is preferred.
Categories
Data EngineeringML Engineering
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.