About ARA's Client – Leading AI & Data Transformation Partner

ARA's Client is a global leader in technology services and consulting, specializing in digital, cloud, and security. They drive innovation across various industries by leveraging cutting-edge AI and data solutions. With a robust commitment to client success and continuous evolution, ARA's Client fosters a collaborative and forward-thinking work environment where impactful solutions are built.

Role Summary

As a Snowflake Data Warehouse- Data Platform Architect, the ideal candidate will lead the end-to-end architecture and engineering of optimized data and AI infrastructure for production machine learning applications. They will design scalable warehouses, Snowpark workloads, and AI-ready data pipelines, ensuring solutions meet high standards for performance, security, and cost-efficiency for ARA's Client's demanding projects.

Key Responsibilities

- Own end-to-end architecture and design of optimized Snowflake data and AI infrastructure, including warehouses, Snowpark workloads, and secure data architecture.
- Design and tune scalable Snowflake warehouses, tasks, streams, Snowpark services, Cortex/AI capabilities, and cloud integrations.
- Serve as an authoritative AI infrastructure expert on Snowflake, applying deep knowledge of Snowflake Data Cloud capabilities and data/AI application patterns.
- Develop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, model serving, and operational complexity.
- Lead architecture assessments and reviews of existing and proposed environments, identifying gaps, risks, bottlenecks, and optimization opportunities.
- Drive architecture decision-making by documenting rationale, trade-offs, assumptions, and dependencies for transparency and alignment.
- Define and maintain AI infrastructure roadmap inputs, capacity planning models, scaling strategies, cost forecasts, and performance improvement opportunities.
- Design deployment, automation, and CI/CD strategies for reliable, repeatable,



and scalable releases of AI systems, models, and data pipelines.
- Establish AI monitoring and observability practices across InfraOps and MLOps, including SLAs, SLOs, alerting, and cost tracking.
- Integrate AI/ML systems into enterprise environments while ensuring interoperability, security, compliance, and regulatory alignment.
- Collaborate with clients, stakeholders, architects, and engineering teams to align infrastructure decisions with business outcomes.
- Set technical direction for workstreams, mentor engineers, review designs/code, and promote engineering best practices across the team.

Must-Have Qualifications

- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- Minimum 12 years of overall experience in data platform architecture, with significant focus on Snowflake.
- At least 4 years of hands-on experience coding, building, monitoring, designing, and operating AI/ML infrastructure or large-scale data platforms.
- Expert-level proficiency with Snowflake warehouses, databases, schemas, secure data sharing, Snowpark, Cortex/AI capabilities, Streams/Tasks, and Streamlit.
- Strong working knowledge of SQL, Python, dbt/Terraform, CI/CD, DataOps, MLOps/AI enablement patterns, observability, and incident response practices.
- Proven experience in architecting scalable data and feature pipelines, AI application integrations, and model-enablement patterns.
- Demonstrated ability to optimize Snowflake AI infrastructure for performance, cost, scalability, security, reliability, and compliance.
- Excellent communication, collaboration, and stakeholder alignment skills.

Nice to Have





- Snowflake certifications such as SnowPro Advanced Architect, SnowPro Advanced Data Engineer, or related AI/data platform credentials.
- Industry experience in BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy, or public sector environments.
- Exposure to advanced Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering, model enablement, and AI application architecture.
- Knowledge of Snowflake governance, secure data sharing, FinOps, infrastructure partner/vendor collaboration, and production support operating models.

Behavioral Competencies

- Strong ownership mindset and accountability for end-to-end architectural solutions.
- Excellent analytical and problem-solving skills in complex and fast-paced technical environments.
- Demonstrated ability to mentor junior engineers and foster a culture of technical excellence and continuous improvement.
- Exceptional communication, presentation, and collaboration skills for effective stakeholder engagement across all levels.
- Strategic thinking with the ability to translate business requirements into robust, scalable technical architectures.
- Adaptability and resilience when navigating evolving AI/ML technologies and client demands.

Why Join Us

- Lead impactful projects at the forefront of AI and data innovation with a global technology leader.
- Work with cutting-edge Snowflake technologies, including Snowpark and Cortex AI, to build advanced infrastructure solutions.
- Collaborate with a diverse team of experts, fostering continuous learning and professional growth within a supportive environment.
- Shape the future of enterprise AI adoption and platform modernization across various industries for ARA's Client.
- Contribute to significant architectural decisions, influencing best practices and technical direction for critical workstreams.
- Benefit from a hybrid work model, offering flexibility and promoting a healthy work-life balance.

Location : PAN India

📌 Snowflake Data Warehouse Architect (Secunderabad)
🏢 ARA Resources
📍 Secunderabad