Data Platform Architect

Accenture PLC; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Accenture is seeking a Data Platform Architect in Pune, India to design and build Snowflake-based AI/ML infrastructure, automate deployment, monitor performance, and ensure secure data access for production analytics workloads. You will collaborate with AI/ML teams and other architects to ensure scalable, compliant and cost-efficient solutions.

The role involves hands-on engineering across data pipelines, feature preparation, model enablement and enterprise integration, with focus on governance,

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Technology or related field.
• Minimum 2 years of experience coding, building, monitoring or troubleshooting AI/ML infrastructure, data platforms, model deployment pipelines or cloud/platform engineering solutions.
• Experience with CI/CD, infrastructure‑as‑code, containers, Kubernetes, workflow orchestration and operational monitoring tools.
• Strong programming/scripting skills in Python, Java, C++, Bash or PowerShell.
• Strong problem‑solving and collaboration in a fast-paced engineering environment.

Responsibilities

• Write, review and debug SQL, Python, scripts and IaC for Snowflake AI/ML infrastructure and deployment tooling.
• Configure Snowflake warehouses, databases, schemas, and secure access patterns.
• Support CI/CD pipelines for Snowflake-based AI solutions using Git, Terraform, dbt, Python, containers and orchestration tools.
• Deploy and operate data pipelines and model-enabled components with reliability, security and cost efficiency.
• Collaborate with data scientists, ML engineers and platform engineers to integrate Snowflake-enabled AI solutions into enterprise systems.
• Document reusable patterns, configuration standards and runbooks for Snowflake-based AI infrastructure.

Skills

Python

SQL

CI/CD

Kubernetes

Infrastructure as Code

Education

Bachelor's degree in Computer Science/Engineering/Information Technology or related field

Tools

Snowflake

Job description

Project Role

Data Platform Architect

Project Role Description

Architects the data platform blueprint and implements the design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : Machine Learning Operations Good to have skills : Snowflake Data Warehouse Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education

Role Summary / Description

AI Powered Tech Talent As a hands‑on Engineer in AI Infrastructure Architecture, you will design, build, automate, monitor and optimize Snowflake-based AI/ML infrastructure for secure data access, feature preparation, model enablement, AI application integration and production analytics workloads. you will work on moderately complex platform components under guidance from senior architects and engineers, contributing to compute optimization, deployment automation, observability, governance, security and operational reliability for AI-driven business solutions.

Key Responsibilities

Write, review and debug SQL, Python, scripts and infrastructure-as-code for Snowflake AI/ML infrastructure, automation, monitoring and deployment tooling. Configure and manage Snowflake warehouses, databases, schemas, secure access patterns, Snowpark workloads, Streamlit apps, model‑related data pipelines and integrations with cloud storage and orchestration tools. Support deployment automation and CI/CD pipelines for Snowflake-based AI solutions using tools such as Git, Terraform, dbt, Python, containers and workflow orchestration tooling where applicable. Deploy and operate data/feature pipelines, AI application integrations and model‑enablement components while applying reliability, security, cost‑efficiency and scalability practices. Monitor warehouse utilization, query performance, pipelines and integration health 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 while meeting compliance and operational requirements. Document reusable patterns, configuration standards and runbooks for Snowflake-based AI infrastructure.

Required Qualifications

Bachelor's degree in Computer Science, Computer Engineering, Information Technology or a related engineering field. Minimum 2 years of experience coding, building, monitoring or troubleshooting AI/ML infrastructure, data platforms, model deployment pipelines or cloud/platform engineering solutions. Strong understanding of AI/ML concepts and the compute, storage, networking, security and deployment foundations required to run AI workloads. Minimum 2 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash or PowerShell. Experience with CI/CD, infrastructure‑as‑code, containers, Kubernetes, workflow orchestration and operational monitoring tools. Strong problem‑solving ability, communication skills and collaboration mindset in a fast‑paced engineering environment.

Required Skills/Experience

Hands‑on experience with Snowflake warehouses, databases, schemas, secure data sharing/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. Working knowledge of SQL, Python, dbt/Terraform, CI/CD pipelines, data observability and cost/performance optimization practices. Ability to optimize warehouses, queries, data pipelines and integrations for performance, reliability, scalability, cost and security. Understanding of MLOps/data platform patterns including feature engineering, model input/output management, monitoring and governance.

Good to Have Skills

Snowflake certification such as SnowPro Core, SnowPro Advanced Architect, SnowPro Data Engineer or related platform credentials. Exposure to industry use cases in BFSI, healthcare, retail/e-commerce, telecom, manufacturing or public sector where data/AI platforms must meet compliance, reliability and data‑governance expectations. Familiarity with Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering and model‑enablement patterns. Knowledge of data governance, data sharing controls, FinOps practices, incident management and production support processes for enterprise AI platforms. 15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation‑led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360 value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360 value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com

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