{"id":4224750,"url":"https://alion.io/job/netscribes-solution-architect-data-engineering-ai","title":"Solution Architect - Data Engineering & AI","company":{"id":1574,"name":"Netscribes","domain":"netscribes.com","url":"https://alion.io/company/netscribes","size_band":"51-200","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":["Bengaluru, India","Pune, India","Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"MLFlow","optional":false},{"name":"Spark","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"AWS Glue","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"dbt","optional":true},{"name":"Power BI","optional":true},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"SQL","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-11-13T06:44:23Z","employer_posted_date":null,"last_verified_at":"2026-11-13T06:44:23Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Key Responsibilities:\n\nClient engagement and discovery:\n\n- Lead technical and business discovery conversations with CXOs, data leaders and architects to understand goals, constraints and the current data landscape.\n\n- Drive credible, consultative technical discussions on data platforms, analytics and AI use cases, and position our point of view against client priorities.\n\nSolution architecture:\n\n- Design end-to-end solutions and reusable frameworks across data ingestion, lakehouse, data modelling, governance, BI and AI/ML on Azure + Databricks or AWS + Databricks.\n\n- Define target-state architectures, migration and modernisation roadmaps, and effort and delivery approaches that delivery teams can execute.\n\n- Run solution reviews, proof-of-concepts and demos with technical and business stakeholders.\n\nDeal ownership, discovery to closure:\n\n- Own the pursuit end to end: discovery, solution design, estimation, proposal or RFP response, pricing inputs, negotiation support and closure.\n\n- Work with Sales, Delivery, Practice and Finance leaders to build winning, deliverable and profitable proposals.\n\n- Maintain pipeline hygiene, deal qualification and win/loss insights.\n\nPractice and delivery enablement:\n\n- Build solution accelerators, reference architectures, case studies and pitch material for the practice.\n\n- Hand over won deals smoothly to delivery, and stay engaged as a trusted advisor to protect scope, quality and client relationships.\n\n- Track hyperscaler and Databricks roadmap changes, and work with partner teams on joint pursuits.\n\nRequired Qualifications and Skills:\n\n- 5 - 8 years of experience, with a strong IT Services or consulting background preferred.\n\n- Proven experience in pre-sales, solutioning or solution management for Data Engineering, Data Analytics and AI engagements.\n\n- Strong understanding of modern data architecture: lakehouse, ELT/ETL, streaming, data modelling, data governance and BI.\n\n- Working experience with Azure + Databricks or AWS + Databricks (for example Delta Lake, Unity Catalog, Spark, workflows and MLflow).\n\n- Demonstrated ability to architect solutions and frameworks, not just describe them.\n\n- Track record of owning deals end to end: discovery, solution, proposal, pricing and closure.\n\n- Excellent communication and presentation skills, with the confidence to lead technical conversations with client architects and senior business stakeholders.\n\n- Strong written skills for proposals, RFP responses and solution documents.\n\n- Ability to work across Sales, Delivery and Practice teams and manage multiple pursuits at once.\n\nGood to Have:\n\n- Hands-on technical experience: PySpark, SQL, Python, or building PoCs and demos on Databricks.\n\n- Exposure to Generative AI, ML and MLOps use cases on Databricks, Azure or AWS.\n\n- Databricks, Azure or AWS certifications (for example Databricks Data Engineer / Architect, Azure Data Engineer, AWS Data Analytics).\n\n- Experience with tools such as Azure Data Factory, Synapse or Fabric, AWS Glue or Redshift, dbt, Power BI or Tableau.\n\n- Experience with cloud migration and data modernisation programmes, such as moving from legacy warehouses to a lakehouse.\n\n- Exposure to Databricks or hyperscaler partner ecosystems and co-sell motions.\nSkills\nSolution Architect, Solution Design, Generative 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