{"id":3370641,"url":"https://alion.io/job/qad-ai-coe-senior-data-engineer-architect","title":"AI CoE Senior Data Engineer & Architect","company":{"id":6493,"name":"QAD","domain":"qad.com","url":"https://alion.io/company/qad","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-11-03T05:54:40Z"}},"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":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":52000,"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":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Azure","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"Google BigQuery","optional":false},{"name":"LookML","optional":false},{"name":"OpenSearch","optional":false},{"name":"pgvector","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"PostgreSQL","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-27T05:28:04Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-11-03T11:27:12Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"QAD is a global leader in cloud-based enterprise solutions, empowering businesses to adapt faster and thrive in an increasingly dynamic, digital world. With a strong focus on innovation and AI-driven insights, QAD is shaping the future of enterprise transformation across industries. We foster a flexible, inclusive culture where bold ideas and future-focused talent to drive real impact. Join us to help build the intelligent, connected enterprise of tomorrow.\nThis hybrid position requires candidates to be based in Pune, with 3-4 days of in-office collaboration per week.\n About the team\nQAD | Redzone is building an enterprise AI platform to support AI-enabled and agentic workflows across the\norganisation. The AI Centre of Excellence (CoE) is accountable for turning that ambition into deployed,\nmeasured, production workflows across priority business functions.\nThe CoE is small, senior and high-leverage. AI Engagement Specialists own the demand side with the\nfunctions; the AI Architect and Senior AI Engineer build the platform and the agents; AI Operations owns the\nrun side. The Senior Data Engineer & Architect owns what every agent depends on: getting the right data to agents, current, governed and in a shape they can use.\nWhy this role exists\nEvery AI use case in the CoE portfolio depends on data: from sales and customer systems, from support and\nengineering knowledge sources, and from delivery and operational systems. Before an agent can use it, that\ndata has to be joined, current, governed and checked against what each user is allowed to see.\nThis role makes data a shared, reusable capability of the AI CoE rather than something rebuilt for each use\ncase. It owns the data layer at feasibility and development) stages and keeps the data running after go-live.\nRole overview\nThe AI CoE Senior Data Engineer & Architect owns the data layer of the AI lifecycle. You will assess data\nfeasibility for each new use case, build and run the pipelines that feed the AI platform, model the semantic\nlayer that agents query instead of raw tables, and make sure every agent sees only the data its user is\nallowed to see.This is a hands-on engineering role with production ownership, measured on agents getting correct, current and permitted data, and on each new use case reaching data-ready faster than the last.\nWhere this role sits\nReports to Head of the AI Centre of Excellence\nWorks with Senior AI Engineer daily; AI Architect on reference architecture; AI\nEngagement Specialist on data feasibility; AI Ops Lead on pipeline health\nand cost; system integrators; data owners in each function; Security and\nGRC\nOwns Data feasibility assessments, AI data pipelines and connectors, semantic\nmodels and metrics for AI use, retrieval-ready knowledge sources, data\naccess patterns for agents, and data freshness and quality targets\nQAD | Redzone - AI CoE Data Engineer · AI Centre of Excellence\nAccountable for Correct, current, governed data for every agent in production, measured\non freshness, quality, reuse of semantic models and time from PRD\napproval to data-ready\nLocation India\n What you will own\n1) Data feasibility and readiness\nAssess the data behind every PRD before build is approved: sources, owners, volumes, quality, access\npaths and gaps, written up as a data readiness view the stage gate can act on, with what is missing, stale\nor not permitted and options to fix it.\nPipelines and integration\nBuild and run the pipelines that feed the AI platform (on AWS today) and the warehouses agents query,\nsuch as BigQuery or Redshift, with incremental and, where it matters, event-driven sync.\nClose freshness gaps: know how long a new record or document takes to reach an agent, set a target\nwith the business, and meet it. Handle deletions and permission changes, not just new records.\nBuild and maintain connectors with the system integrators, so each new source is added once and\nreused across use cases.\nSemantic layer\nModel the business entities and metrics agents need in the semantic layer, so agents query governed\ndefinitions agreed with data owners, consistent with what dashboards report, instead of writing SQL\nagainst raw tables.\nPut guardrails on structured queries: read-only access, row limits, timeouts and cost limits for any agent\nthat queries data.\n2) Retrieval-ready knowledge\nPrepare unstructured sources for retrieval with the Senior AI Engineer: metadata, release and version\ntags, access tags, and structure that keeps the source context intact; build and maintain the golden\ndatasets used to test retrieval and answer quality.\nData access, security and governance\nMake agents act as the user: user-scoped access, row and column-level security in the semantic layer,\nand no over-privileged shared service accounts.\nHandle sensitive data properly with Security and GRC: classification, masking of personal and customer\ndata in tickets, residency rules for regulated regions, lineage and audit evidence.\nRun and improve (L5)\nOwn pipeline health in production: freshness and quality monitoring, alerts someone acts on, and fast\nrecovery when a source system changes its schema; with AI Ops, keep processing, storage and\nembedding spend per use case in check.\nTurn each build into reusable data products so the next use case starts from shared models and\nconnectors, not from scratch.\n Essential\n8+ years in data engineering, including at least 3 years building data for ML, analytics or Gen AI products\nrunning in production.\nStrong SQL and Python, and pipeline orchestration in practice, for example Airflow, dbt, AWS Glue or\nsimilar.\nCloud data platforms: Azure , AWS (S3, Glue, Redshift, RDS) and/or Google BigQuery.\nSemantic and dimensional modelling: hands-on with a semantic or metrics layer such as Cube, dbt\nSemantic Layer, LookML or Power BI semantic models.\nIncremental and event-driven ingestion: change data capture, webhooks or streaming, and handling\ndeletes and late-arriving data.\nData for retrieval: document ingestion, metadata design and hybrid or vector search (for example\nOpenSearch, Elasticsearch or pgvector), and enough understanding of embeddings to work with an AI\nengineer.\nData security in practice: role-based access, row and column-level security, handling personal data, and\ncloud identity and access management.\nAPI integration with enterprise SaaS, such as CRM and Atlassian REST APIs.\nData quality discipline: tests, freshness and quality monitoring, and service-level targets for data.\nClear communication with data owners and business teams: able to explain what the data can and\ncannot support, and why.\nData depth\nWe are looking for someone who has run pipelines in production and lived with the consequences, and can\ntell when an agent's wrong answer is really a data problem.\nStrongly preferred\nSales and customer data, support and engineering knowledge data, or ERP and manufacturing data;\nProgress OpenEdge familiarity is a plus.\nExperience with an enterprise RAG or AI platform, and with exposing data to agents through APIs or\nMCP tools.\nWorking alongside system integrators and a central data team, and across time zones; enterprise B2B\nSaaS experience.\n\nWhat this role is not\nNot a BI developer. Dashboards are owned by the functions and AI Ops; you make the data behind them\nand the agents trustworthy.\nNot the owner of the enterprise data platform. You work with the central data team and reuse their\nassets, and build what AI use cases need on top.\nNot an AI engineer. Agent logic, prompts and models sit with the Senior AI Engineer; you own the data\nthey depend on.\nQAD | Redzone - AI CoE Data Engineer · AI Centre of Excellence\nNot a one-off integration contractor. You own the pipelines and semantic models in production, after\ngo-live.\nWhat success looks like\nFirst 3 months\nData feasibility assessments completed for the priority use cases.\nA data readiness checklist built into the stage gates and used on every new use case.\nAn agreed access pattern with Security for user-scoped data, and freshness measured for priority data\nsources.\nSemantic layer version 1 live for the priority domain, used by production agents.\nFreshness and quality targets set and monitored for every production data source.\nYour health and well being are important to us at QAD. We provide programs that help you strike a healthy work-life balance.\nOpportunity to join a growing business, launching into its next phase of expansion and transformation.\nCollaborative culture of smart and hard-working people who support one another to get the job done.\nAn atmosphere of growth and opportunity, where idea-sharing is always prioritized over level or hierarchy.\nCompensation packages based on experience and desired skill set\nAbout QAD:\nQAD | Redzone is redefining manufacturing and supply chains through its intelligent, adaptive platform that connects people, processes, and data into a single System of Action. With three core pillars - Redzone (frontline empowerment), Adaptive Applications (the intelligent backbone), and Champion AI (Agentic AI for manufacturing) - QAD | Redzone helps manufacturers operate with Champion Pace, achieving measurable productivity, resilience, and growth in just 90 days.\nQAD is committed to ensuring that every employee feels they work in an environment that values their contributions, respects their unique perspectives and provides opportunities for growth regardless of background. QAD’s DEI program is driving higher levels of diversity, equity and inclusion so that employees can bring their whole self to work.\nWe are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.","description_format":"text","description_chars":9837,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Equity"],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["ERP & Business Management Software","Supply Chain & Logistics Software","Manufacturing & Industrial Software"],"lifecycle":[{"event":"open","at":"2026-10-28T00:49:38Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":7,"expected_fill_days":31,"reasons":["conf:3","velocity","win:early"],"computed_at":"2026-11-03T05:54:40Z"},"pay":null,"html_url":"https://alion.io/job/qad-ai-coe-senior-data-engineer-architect","json_url":"https://alion.io/job/qad-ai-coe-senior-data-engineer-architect.json","meta":{"generated_at":"2026-11-03T12:56:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":17839,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-04T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":6493},"rest":"https://alion.io/mcp/rest/get_company?id=6493"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fqad-ai-coe-senior-data-engineer-architect"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fqad-ai-coe-senior-data-engineer-architect"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fqad-ai-coe-senior-data-engineer-architect"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/qad-ai-coe-senior-data-engineer-architect\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fqad-ai-coe-senior-data-engineer-architect"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3370641}},{"tool":"search_jobs","arguments":{"company":"qad.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3370641},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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