{"id":1167883,"url":"https://alion.io/job/jpmorganchase-senior-lead-data-architect-information-architecture","title":"Senior Lead Data Architect: Information Architecture","company":{"id":257,"name":"JPMorganChase","domain":"jpmorganchase.com","url":"https://alion.io/company/jpmorganchase","size_band":"5000+","is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":100,"open_postings":358,"ghost_share":0.006,"stale_share":0.008,"repost_share":0.017,"time_to_fill_p50_days":3,"computed_at":"2026-09-24T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Plano, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":126000,"max_usd":248000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":178},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":true}],"status":"live","first_seen_at":"2026-09-24T04:25:14Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-09-25T00:37:46Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"You strive to be an essential member of a diverse team of visionaries dedicated to making a lasting impact. Don’t pass up this opportunity to collaborate with some of the brightest minds in the field and deliver best-in-class solutions to the industry.\nAs a Senior Lead Data Architect, Data Modelling at JPMorganChase within Enterprise Platforms (Employee Platforms) in Corporate Technology, you shape how data is structured, defined, and trusted across products that serve critical employee experiences. You will lead the domain’s data modelling strategy across transactional, analytical, streaming, and AI-driven consumption patterns, ensuring performance, clarity, and safe evolution. You will also help establish semantic foundations so teams and enterprise-authorized AI capabilities can interpret and use data reliably with appropriate validation, security, resiliency, and auditability.\nJob responsibilities\nLead the end-to-end data modelling strategy for the domain, aligning logical and physical models to the needs of each product and consumer.\nDesign and optimize models across raw/denormalized document structures, OLTP relational (3NF), OLAP dimensional (star/snowflake), and event/message schemas.\nDefine and maintain semantic foundations, including a data dictionary, naming and namespace conventions, and attribute-level abstractions to support interoperability.\nGovern schema evolution and model versioning to enable safe change while protecting downstream consumers through clear contracts and lineage expectations.\nRepresent data architecture and modelling at governance forums, improving standards and guiding technology evaluation against established frameworks.\nProvide technical direction and mentorship to engineering teams, contractors, and vendors as a domain subject matter expert in data modelling.\nDevelop and review secure, high-quality DDL and model-implementing transformation logic, debugging issues and improving production readiness.\nDrive modelling decisions that influence product design, application functionality, analytics outcomes, access-pattern performance, and operational stability.\nUse enterprise-authorized AI capabilities to accelerate modelling analysis and documentation while validating outputs and aligning to data sensitivity, security controls, resiliency, and auditability expectations.\nChampion reuse-first, AI-assisted validation and agentic workflows within the software development lifecycle to strengthen quality checks, documentation, traceability, and model usability for both people and AI systems.\nRequired qualifications, capabilities and skills\nFormal training or certification on data architecture and data modelling concepts and 5+ years applied experience.\nExtensive hands-on experience designing and delivering optimized data models across raw/document, OLTP 3NF, OLAP dimensional, and event/message schema patterns.\nStrong command of core data concepts, including entities, relationships, cardinality, normalization vs. denormalization trade-offs, attribute abstraction, and schema evolution.\nPractical experience delivering system design, application development, testing, and operational stability in production environments.\nSolid understanding of modern lakehouse and data and analytics platforms, including Databricks (Delta Lake, Unity Catalog, medallion architecture) or equivalent platforms.\nDemonstrated experience using enterprise-authorized AI capabilities to support data modelling and architecture workflows, with strong validation habits and awareness of data sensitivity.\nAbility to assess and validate AI-assisted modelling recommendations before adoption, escalating uncertainty and ensuring alignment to security, auditability, and resiliency expectations.\nAdvanced knowledge in one or more programming languages and technical disciplines (e.g., cloud, AI/ML, data platforms), with strong architecture and engineering fundamentals.\nProven ability to independently solve complex data model design and functionality problems with little to no oversight.\nPreferred qualifications, capabilities and skills\nDeep specialization in data modelling, including the ability to explain and teach model-shape decisions based on consumption patterns.\nExperience defining and sustaining a shared business glossary and semantic layer that stays coherent across domains, including for AI-driven consumption.\nStrong, current experience optimizing analytical/dimensional models on Databricks or comparable cloud-native data platforms, including performance and cost considerations at scale.\nFamiliarity with vector and graph modelling and retrieval patterns for AI/ML and agentic consumption, in addition to traditional OLTP and OLAP modelling.\nPractical fluency integrating agentic AI workflows into modelling, documentation, and data quality processes, including effective prompting and rigorous validation.\nExperience establishing or scaling modelling standards, naming conventions, and governance practices, including onboarding and mentoring other modelers and engineers.\nExposure to schema/contract-driven development (e.g., data contracts, schema registries) and managing schema evolution safely in production.","description_format":"text","description_chars":5187,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Credit Cards","Wealth Management","Asset Management","Payments"],"lifecycle":[{"event":"open","at":"2026-09-24T04:47:02Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":3,"reasons":["conf:0","velocity","win:early","comp:brand"],"computed_at":"2026-09-24T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/jpmorganchase-senior-lead-data-architect-information-architecture","json_url":"https://alion.io/job/jpmorganchase-senior-lead-data-architect-information-architecture.json","meta":{"generated_at":"2026-09-25T00:56:46Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":862,"day_limit":5000,"remaining_today":4138,"minute_limit":60,"resets_at":"2026-09-26T00:00:00Z"}}}