{"id":3064254,"url":"https://alion.io/job/ge-vernova-ai-data-architect","title":"AI Data Architect","company":{"id":6165,"name":"GE Vernova","domain":"gevernova.com","url":"https://alion.io/company/ge-vernova","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":83,"open_postings":406,"ghost_share":0.005,"stale_share":0.65,"repost_share":0.032,"time_to_fill_p50_days":27,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":32000,"max_usd":60000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"Feature Store","optional":false},{"name":"Fivetran","optional":false},{"name":"LLM","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Power BI","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-10-05T00:00:00Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-31T18:48:52Z","board_verified":true,"closed_at":null,"days_open":27,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":27},"description":"Job Description Summary\nWe are seeking a senior AI Data Architect to lead the architectural direction, standards, and design governance of our Data & Analytics platform. This role sits at the intersection of enterprise architecture, data engineering, and AI data readiness, and is suited to a senior individual contributor who can guide platform evolution, validate solution designs, and influence technical decisions across multiple teams. The environment is AWS-based, centered on Redshift, and supports ingestion, orchestration, modeling, BI consumption, and emerging AI/ML and LLM use cases across a complex enterprise landscape.Job Description\nThe AI Data Architect will play a key role in shaping and governing the evolution of the enterprise Data & Analytics platform, with a particular focus on preparing the platform and its data assets to support advanced analytics, AI/ML, and LLM-driven use cases. Working across platform engineering, data engineering, data modeling, analytics, governance, and business stakeholders, this role will define architectural standards and guardrails, review and validate solution designs, and help teams adopt scalable and sustainable patterns.\nThe platform operates in an AWS environment with Redshift as the core analytical data platform. Data is ingested through HVR (Fivetran) and internally developed batch ingestion applications, orchestrated through an in-house tool, and consumed through Tableau and Power BI. Within this context, the AI Data Architect will provide direction across ingestion, orchestration, modeling, BI consumption, governance, operational maturity, and AI-oriented data enablement.\nKey Responsibilities\nProvide architectural leadership for the Data & Analytics platform, including target-state direction, principles, standards, and guardrails\nGuide the evolution of the AWS-based analytics environment, with particular focus on Redshift architecture, scalability, reliability, maintainability, and performance\nDefine and maintain best practices across ingestion, orchestration, data modeling, BI consumption, platform usage, and AI data readiness\nReview, challenge, and validate solution designs proposed by development teams to ensure alignment with platform standards and enterprise architectural principles\nSupport governance and quality improvement through practical architecture review, design oversight, and standards adoption\nHelp shape platform capabilities that improve data readiness for AI/ML and LLM-related use cases, including metadata quality, discoverability, governed reuse, lineage visibility, and fit-for-purpose data preparation\nProvide guidance on modern data architecture patterns relevant to AI enablement, including lakehouse architecture, feature stores, vector database concepts, and related design considerations where appropriate\nPromote effective use of metadata, cataloging, and governance capabilities to improve data discovery, trust, interoperability, and cross-platform connectivity\nCollaborate with platform, engineering, analytics, governance, and business stakeholders to align technical direction with enterprise priorities and delivery needs\nFacilitate cross-team design discussions, technical decision-making, and trade-off analysis across multiple teams and stakeholders\nMeasures of Success\nImproved architectural consistency across teams and platform domains\nHigher quality, more scalable, and more maintainable solution designs\nStronger adoption of platform standards, guardrails, and best practices\nImproved coordination between platform, development, and data modeling teams\nStronger governance and better technical decision quality across the platform\nImproved reliability, maintainability, and long-term sustainability of the environment\nBetter metadata quality, discoverability, lineage visibility, and governance to support analytics and AI-ready data usage\nImproved readiness of data assets and platform capabilities for AI/ML and LLM-related use cases\nEffective support of strategic initiatives that require cross-team architectural leadership and coordination\nRequired Qualifications\n6-8 years of experience in a similar AI data architecture, platform architecture, data architecture, solution architecture, platform engineering, or senior data engineering role within a cloud-based Data & Analytics environment\nStrong experience with AWS services and architectural principles relevant to enterprise data and analytics platforms\nStrong understanding of Redshift-based analytical data environments\nExperience across key Data & Analytics capabilities, including ingestion, orchestration, data modeling, analytics consumption, and platform operations\nDemonstrated ability to define standards, architectural patterns, and design guardrails across multiple teams\nProven experience reviewing, challenging, and validating technical solutions proposed by engineering and data teams\nPractical working knowledge of SQL and analytics tools sufficient to assess technical designs and engage credibly with delivery teams\nFamiliarity with modern data architecture patterns that support AI/ML use cases, including lakehouse architecture, feature stores, and vector database concepts\nPractical understanding of data preparation, metadata, governance, and discoverability needs that support downstream AI, ML, and LLM use cases\nPreferred Qualifications\nExperience with HVR and/or Fivetran in enterprise ingestion environments\nFamiliarity with Tableau and Power BI in governed analytics ecosystems\nExperience with data fabric, data mesh, or other distributed data architecture models, including decentralized ownership and federated governance\nExperience with modern metadata, catalog, lineage, or governance platforms that improve discovery and interoperability\nExperience improving metadata management, cataloging, governance processes, or platform transparency\nExperience with enterprise architecture practices, platform modernization, or operating model improvement\nExposure to AI/ML platform enablement patterns, including governed data provisioning for LLM use cases\nCertifications in AWS, architecture, data engineering, or project/program management\nExperience participating in architecture review boards, design authorities, or technical governance forums\nAdditional Information\nRelocation Assistance Provided: Yes","description_format":"text","description_chars":6326,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Relocation assistance"],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Hydroelectric","Power Grid","Industrial Machinery","Wind 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