{"id":3318527,"url":"https://alion.io/job/quiddity-software-solutions-senior-solution-architect-data-engineering","title":"Senior Solution Architect - Data Engineering","company":{"id":4479787,"name":"QUIDDITY SOFTWARE SOLUTIONS","domain":"quiddityinfotech.com","url":"https://alion.io/company/quiddity-software-solutions","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":37},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Cortex","optional":false},{"name":"Cursor","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Fivetran","optional":false},{"name":"Git","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-10-27T06:15:08Z","employer_posted_date":null,"last_verified_at":"2026-10-27T06:15:08Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Senior Solutions Architect - Data\n\nRole Type : Customer-Facing Architecture and Hands-on Technical Delivery\n\nAbout the Role :\n\nWe are seeking a Senior Solutions Architect - Data to lead customer engagements and deliver end-to-end data and AI solutions, from discovery and solution design through implementation, production deployment, and adoption.\n\nThe ideal candidate combines strong customer-facing solution architecture skills with hands-on expertise in data engineering, Snowflake, modern data transformation frameworks, semantic modeling, and AI-enabled analytics. The role requires translating complex business requirements into scalable, secure, and cost-effective technical solutions while accelerating development through AI-assisted coding tools.\n\nThe candidate will work closely with business stakeholders, executives, data teams, and technology leaders to build trusted data foundations, enable self-service analytics, and deliver AI-driven business outcomes across Go-to-Market (GTM), revenue operations, and enterprise functions.\n\nKey Responsibilities :\n\nCustomer Engagement and Solution Architecture :\n\n- Lead customer discovery sessions, technical workshops, and stakeholder interviews to understand business processes, data challenges, and desired outcomes.\n\n- Translate business requirements into solution architectures, implementation roadmaps, technical specifications, and measurable success criteria.\n\n- Present architectural decisions, technical trade-offs, and recommendations to business users, technology teams, and executive stakeholders.\n\n- Own the technical solution lifecycle from proof of concept (PoC) and prototyping through production deployment and customer adoption.\n\n- Identify opportunities to improve business processes through data modernization, analytics, and AI-enabled workflows.\n\nData Engineering and Snowflake Architecture :\n\n- Design and implement end-to-end data solutions covering ingestion, transformation, data modeling, semantic layers, analytics, and AI applications.\n\n- Develop and optimize advanced SQL queries, Snowflake data models, transformation pipelines, and incremental processing workflows.\n\n- Implement scalable data architectures with appropriate performance optimization, access controls, data quality checks, and cost management.\n\n- Design reliable pipelines with testing, documentation, lineage, observability, and deployment controls.\n\n- Establish engineering best practices for data reliability, maintainability, security, and production operations.\n\nData Transformation and Integration :\n\n- Develop and maintain data transformation workflows using dbt and SQLMesh, including models, dependencies, tests, environments, and deployment strategies.\n\n- Integrate Salesforce and other enterprise applications to establish trusted data models for accounts, opportunities, contracts, subscriptions, and customer activities.\n\n- Build data ingestion and integration workflows using Python, REST APIs, and tools such as Fivetran or Airbyte.\n\n- Implement appropriate reconciliation, data validation, error handling, and monitoring mechanisms.\n\n- Collaborate with source-system owners to resolve data quality issues and ensure consistency across integrated platforms.\n\nSemantic Modeling and AI-Powered Analytics :\n\n- Design governed semantic layers that define business metrics, entities, relationships, terminology, and approved calculation logic.\n\n- Enable natural-language analytics and conversational data exploration using Snowflake Cortex Analyst and related AI capabilities.\n\n- Ensure business metrics are consistent, traceable, and validated across reporting, analytics, and AI applications.\n\n- Validate AI-generated SQL for correctness, business alignment, security, and performance.\n\n- Implement appropriate grounding, evaluation, access controls, and guardrails to improve the reliability of AI-generated insights.\n\nAI-Assisted Development and Engineering Productivity :\n\n- Use AI-assisted development tools such as Cursor, Claude Code, OpenAI Codex, or equivalent tools to accelerate prototyping, coding, testing, debugging, and documentation.\n\n- Apply AI-assisted engineering practices while maintaining code quality, security, maintainability, and compliance with customer requirements.\n\n- Develop and integrate AI-enabled workflows using LLMs, AI agents, retrieval-augmented generation (RAG), and enterprise data sources.\n\n- Establish disciplined practices for code review, automated testing, version control, and protection of sensitive customer information.\n\n- Evaluate emerging AI development capabilities and identify opportunities to improve engineering productivity and solution delivery.\n\nSolution Demonstration and Production Delivery :\n\n- Build functional prototypes and business-focused demonstrations to validate solution feasibility and communicate business value.\n\n- Incorporate customer feedback and iteratively refine solutions before production implementation.\n\n- Own technical troubleshooting, user acceptance testing (UAT), release planning, go-live readiness, and production stabilization.\n\n- Implement Git-based development workflows, CI/CD pipelines, environment management, and controlled releases.\n\n- Communicate technical progress, dependencies, risks, issues, and mitigation plans to customer and internal stakeholders.\n\nCustomer Adoption and Business Value :\n\n- Lead customer onboarding, technical enablement, training, and knowledge transfer.\n\n- Drive adoption of delivered data products, analytics solutions, and AI-enabled workflows.\n\n- Define and track adoption metrics, usage patterns, operational improvements, and business outcomes.\n\n- Identify opportunities for continuous improvement, solution expansion, and additional data and AI use cases.\n\nRequired Skills and Qualifications :\n\nPrimary Technical Skills :\n\n1. Solution Architecture and Customer Engagement :\n\n- Strong experience in customer-facing solution architecture, technical consulting, or solution engineering.\n\n- Proven ability to lead discovery workshops and translate ambiguous business requirements into practical technical solutions.\n\n- Excellent communication, stakeholder management, presentation, and technical problem-solving skills.\n\n- Experience owning solution delivery from requirements gathering through production adoption.\n\n2. Snowflake and Advanced SQL :\n\n- Deep hands-on experience with Snowflake architecture, data engineering, and analytics solutions.\n\n- Strong command of advanced SQL, including complex joins, CTEs, window functions, query optimization, and performance tuning.\n\n- Experience with dimensional modeling, incremental processing, data transformations, and large-scale analytical workloads.\n\n- Knowledge of Snowflake security, role-based access control, workload optimization, and cost management.\n\n- Understanding of Snowflake Cortex capabilities and their application to enterprise analytics and AI use cases.\n\n3. dbt and SQLMesh :\n\n- Strong hands-on experience with dbt for modular data transformations, reusable models, testing, documentation, and dependency management.\n\n- Working knowledge of SQLMesh, including model definitions, incremental processing, environments, testing, and deployment.\n\n- Understanding of version-controlled data development, CI/CD, data quality validation, and production release management.\n\n4. Data Integration and Engineering :\n\n- Experience integrating Salesforce and other enterprise systems with analytical data platforms.\n\n- Knowledge of Salesforce objects and business entities, including accounts, contacts, leads, opportunities, contracts, and subscriptions.\n\n- Proficiency in Python, REST APIs, and data integration patterns.\n\n- Experience with ingestion and ELT platforms such as Fivetran, Airbyte, or equivalent tools.\n\n- Ability to design reliable, scalable, and maintainable data pipelines.\n\n5. Semantic Modeling and Business Analytics :\n\n- Practical experience defining business metrics, dimensions, entities, relationships, and reusable semantic models.\n\n- Understanding of governed metrics and semantic layers for BI, self-service analytics, and natural-language querying.\n\n- Ability to validate generated SQL and ensure analytical outputs align with approved business definitions.\n\n- Experience translating business terminology into technical data models and analytical logic.\n\n6. AI, LLMs, and AI-Assisted Development :\n\n- Working knowledge of LLMs, prompt engineering, AI agents, RAG, and natural-language analytics.\n\n- Understanding of grounding, evaluation, hallucination mitigation, data privacy, and AI guardrails.\n\n- Hands-on experience with AI coding assistants such as Cursor, Claude Code, Codex, or equivalent tools.\n\n- Ability to use AI-assisted development responsibly with code reviews, automated tests, and secure engineering practices.\n\n7. Software Engineering and Production Delivery :\n\n- Strong working knowledge of Git, branching strategies, pull requests, CI/CD, and automated testing.\n\n- Experience managing development, testing, staging, and production environments.\n\n- Understanding of application security, observability, troubleshooting, release management, and production support.\n\nB. Business and Domain Knowledge :\n\n- Understanding of Go-to-Market (GTM), sales operations, revenue operations, and enterprise business processes.\n\n- Ability to collaborate with business teams to define KPIs, reporting requirements, and operational metrics.\n\n- Experience connecting business objectives with data architecture and AI implementation strategies.\n\n5. Preferred Domain Knowledge :\n\nExperience in one or more of the following functional areas is highly desirable :\n\nSales and Revenue Operations :\n\n- Sales pipeline management, forecasting, conversion rates, bookings, opportunity tracking, and renewals.\n\nFinance :\n\n- Annual recurring revenue (ARR), monthly recurring revenue (MRR), revenue movements, financial reconciliation, and reporting.\n\nMarketing :\n\n- Campaign performance, marketing attribution, funnel conversion, customer acquisition costs, and campaign ROI.\n\nCustomer Success :\n\n- Customer health scoring, churn prediction, retention, renewal forecasting, and account expansion.\n\nProfessional Services :\n\n- Resource utilization, project delivery, services revenue, billing, delivery efficiency, and project profitability.\n\n6. Preferred Additional Qualifications :\n\n- Experience delivering enterprise data platforms and AI-enabled analytics solutions for external customers.\n\n- Exposure to Snowflake Cortex Analyst, Cortex AI, or comparable natural-language analytics capabilities.\n\n- Familiarity with modern BI and analytics platforms and governed metric definitions.\n\n- Experience with data observability, lineage, governance, and enterprise data quality frameworks.\n\n- Experience delivering proofs of concept and converting them into production-grade enterprise solutions.\n\n- Relevant cloud data platform or architecture certifications are an advantage.\n\n7. Expected Deliverables :\n\n- Customer discovery outcomes, documented requirements, and solution architecture designs.\n\n- Production-ready Snowflake data models, transformation pipelines, and integration workflows.\n\n- Governed semantic models and validated business metrics for analytics and AI use cases.\n\n- Functional prototypes, technical demonstrations, and production deployments.\n\n- Automated testing, documentation, CI/CD workflows, and operational support procedures.\n\n- Customer onboarding materials, training, and adoption measurement.\n\n- Demonstrable improvements in data reliability, analytics accessibility, engineering productivity, and business outcomes.\n\n8. Success Measures :\n\n- Successful conversion of business requirements into production-ready solutions.\n\n- Data quality, reliability, performance, security, and cost efficiency of delivered solutions.\n\n- Accuracy and consistency of semantic models, business metrics, and AI-generated analytical outputs.\n\n- Reduction in prototype-to-production delivery time through effective engineering...","description_format":"text","description_chars":13225,"description_truncated":true,"requirements":{"experience_years_min":15,"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":[],"lifecycle":[{"event":"open","at":"2026-10-27T06:29:10Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":31,"reasons":["seen:0","win:early"],"computed_at":"2026-10-27T15:16:47Z"},"pay":null,"html_url":"https://alion.io/job/quiddity-software-solutions-senior-solution-architect-data-engineering","json_url":"https://alion.io/job/quiddity-software-solutions-senior-solution-architect-data-engineering.json","meta":{"generated_at":"2026-10-27T15:16:47Z","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":4204,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-28T00:00:00Z"}},"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":4479787},"rest":"https://alion.io/mcp/rest/get_company?id=4479787"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fquiddity-software-solutions-senior-solution-architect-data-engineering"},{"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%2Fquiddity-software-solutions-senior-solution-architect-data-engineering"},{"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%2Fquiddity-software-solutions-senior-solution-architect-data-engineering"},{"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/quiddity-software-solutions-senior-solution-architect-data-engineering\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fquiddity-software-solutions-senior-solution-architect-data-engineering"}]}