{"id":3270042,"url":"https://alion.io/job/accenture-data-platform-architect-10","title":"Data Platform Architect","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2115,"ghost_share":0.001,"stale_share":0.165,"repost_share":0.006,"time_to_fill_p50_days":5,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Snowflake","optional":false},{"name":"AI Agents","optional":true},{"name":"Airflow","optional":true},{"name":"C++","optional":true},{"name":"CI/CD","optional":true},{"name":"Cortex","optional":true},{"name":"dbt","optional":true},{"name":"FinOps","optional":true},{"name":"Java","optional":true},{"name":"Kubeflow","optional":true},{"name":"Machine Learning","optional":true},{"name":"PowerShell","optional":true},{"name":"Prometheus","optional":true},{"name":"Python","optional":true},{"name":"SLI/SLO/SLA","optional":true},{"name":"SQL","optional":true},{"name":"Streamlit","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-23T00:00:00Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-11-04T11:33:21Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"Project Role : Data Platform ArchitectProject 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.\nMust have skills : Snowflake Data Warehouse\nGood to have skills : AI Agents & Workflow Integration\nMinimum 7.5 year(s) of experience is required\nEducational Qualification : 15 years full time education\nRole Summary / Description\nAI Powered Tech Talent\nAs a Senior Engineer in AI Infrastructure Architecture for Snowflake, you will own significant portions of the end-to-end architecture and engineering of optimized data and AI infrastructure for production machine learning and AI-enabled applications. You will design scalable warehouses, Snowpark workloads, AI-ready data/feature pipelines, model-enablement patterns, automation and operational controls that align with client standards, SLAs, security, compliance and cost-efficiency expectations. You will bring industry experience across enterprise AI adoption, platform modernization, regulated data workloads, FinOps and production reliability, while mentoring engineers and partnering with architects to translate business requirements into robust Snowflake-based AI infrastructure solutions.\nKey Responsibilities\nOwn end-to-end architecture and design of optimized Snowflake data and AI infrastructure, including warehouses, Snowpark workloads, secure data architecture, AI-ready feature/data pipelines, model integration and AI application enablement.\nDesign and tune scalable Snowflake warehouses, tasks, streams, Snowpark services, Cortex/AI capabilities, Streamlit applications and cloud integrations, including compute sizing, query optimization, governance, access controls and high-throughput data access design.\nServe as an authoritative AI infrastructure expert on Snowflake, applying deep knowledge of Snowflake Data Cloud capabilities, data/AI application patterns, governance, security and cost levers.\nDevelop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, model serving, observability, security, compliance, cost and operational complexity.\nLead architecture assessments and reviews of existing and proposed environments, identifying gaps, risks, bottlenecks and optimization opportunities, and recommending remediation actions.\nDrive architecture decision-making by documenting rationale, trade-offs, assumptions and dependencies so decisions are transparent, defensible and aligned with business SLAs and standards.\nDefine and maintain AI infrastructure roadmap inputs, capacity planning models, scaling strategies, cost forecasts and performance improvement opportunities.\nDesign deployment, automation and CI/CD strategies for reliable, repeatable and scalable releases of AI systems, models, data pipelines and platform components into production.\nEstablish AI monitoring and observability practices across InfraOps and MLOps, including SLAs, SLOs, alerting, performance/cost tracking and continuous optimization.\nIntegrate AI/ML systems into enterprise environments while ensuring interoperability, security, compliance, regulatory alignment and adherence to client standards.\nCollaborate with clients, stakeholders, architects and engineering teams to align infrastructure decisions with business outcomes and translate requirements into actionable architecture standards.\nSet technical direction for workstreams, mentor engineers, review designs/code and promote engineering best practices across the team.\nRequired Qualifications\nBachelor's degree in Computer Science, Computer Engineering, Information Technology or a related engineering field.\nMinimum 4 years of experience coding, building, monitoring, troubleshooting, designing and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines or large-scale engineering solutions.\nStrong understanding of AI/ML concepts and the computing infrastructure required to deploy, run and optimize production AI workloads.\nMinimum 4 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, PowerShell or equivalent engineering languages.\nExperience with data pipeline and workflow management tools such as Apache Airflow, Kubeflow, managed orchestration services or platform-native workflow tooling.\nStrong problem-solving skills and ability to work in a fast-paced engineering or client delivery environment.\nExcellent communication, collaboration and stakeholder alignment skills.\nMinimum 4 years of experience in AI/ML infrastructure engineering or related roles on a hyperscaler or enterprise platform for deploying large-scale solutions.\nProven experience leading AI projects or engineering workstreams and managing priorities across multiple initiatives.\nDemonstrated experience evaluating and selecting AI technologies, frameworks, cloud services and architecture patterns.\nRequired Skills/ Experience\nStrong hands-on experience with Snowflake warehouses, databases, schemas, secure data sharing/access controls, Snowpark, Cortex/AI capabilities, Streams/Tasks, Streamlit and cloud ecosystem integrations.\nExperience architecting scalable data and feature pipelines, AI application integrations, model-enablement patterns, governance, query/warehouse optimization and secure data access.\nStrong working knowledge of SQL, Python, dbt/Terraform, CI/CD, DataOps, MLOps/AI enablement patterns, observability and incident response practices.\nAbility to optimize Snowflake AI infrastructure for performance, cost, scalability, security, reliability and compliance.\nExperience producing architecture decision records, reference implementations, standards, runbooks and reusable platform patterns.\nGood to Have Skills\nSnowflake certifications such as SnowPro Advanced Architect, SnowPro Advanced Data Engineer or related AI/data platform credentials.\nIndustry experience in BFSI, healthcare, retail/e-commerce, telecom, manufacturing, energy or public sector environments where data/AI platforms must meet compliance, security, reliability and cost-control requirements.\nExposure to Snowpark, Cortex/AI features, vector search, retrieval pipelines, feature engineering, model enablement and AI application architecture.\nKnowledge of Snowflake governance, secure data sharing, FinOps, infrastructure partner/vendor collaboration and production support operating models.\n15 years full time educationAbout Accenture\nAccenture 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 atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, militaryveteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicablelaw. 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