Solution Architect – Data Analytics (Presales)

We are looking for aSolution Architect cum Presales Leaderwith deep expertise inData Engineering, Analytics, and AI/ML solutions . This role requires a unique blend oftechnical architecture, presales solutioning, and client engagement skillsto help win new business opportunities, design scalable solutions, and enable delivery excellence across global clients.Key Responsibilities Presales & Client Engagement Partner with sales and business teams to identify opportunities in Data Engineering, Analytics, BI, and AI/ML. Conduct discovery workshops with clients to understand pain points, data landscape, and business objectives. Prepare winning RFP/RFI responses, solution decks, cost models, and PoCs. Deliver demos, technical presentations, and thought leadership sessions to CXO and senior stakeholders. Define value propositions, ROI models, and differentiators for data/analytics opportunities. Solution Architecture & Design Design end-to-end Data & Analytics architectures including: Data Engineering: ingestion, pipelines, ETL/ELT, data lakes, warehouses, lakehouses. Analytics: BI dashboards, reporting, self-service analytics, advanced analytics. AI/ML Integration: predictive, prescriptive, NLP, GenAI, and data-driven automation. Define reference architectures leveraging modern platforms (Snowflake, Databricks, BigQuery, Synapse, Redshift, etc.). Architect scalable solutions on AWS, Azure, or GCP cloud ecosystems. Ensure security, compliance, and data governance are embedded in solutions. Build reusable assets, accelerators, and frameworks for faster presales cycles. Delivery Enablement & Governance Collaborate with delivery leads to ensure solution feasibility and alignment. Provide technical governance during transition/mobilization phases. Define SLAs, KPIs, and governance frameworks for data & analytics programs. Support estimation of efforts, resources, and delivery planning. Innovation & Thought Leadership Drive innovation in AI/ML, GenAI for data, and modern data architectures (lakehouse, data mesh). Mentor solution consultants and delivery architects on presales and solutioning best practices. Represent the organization in conferences, client forums, and leadership workshops.Key Performance Indicators (KPIs) Win ratio on data/analytics opportunities supported. Revenue growth influenced by data/analytics deals. Solution accuracy vs. delivery execution (variance ≤ 10%). Number of PoCs, accelerators, and reusable assets created. Customer CSAT/NPS for delivered data programs.Required Skills & Qualifications Technical Skills Strong expertise in Data Engineering: ETL/ELT, data lakes, warehouses, real-time streaming (Kafka, Kinesis, Spark, Flink). Proficiency in Analytics & BI tools: Power BI, Tableau, Qlik, Looker. Knowledge of Data Science/AI frameworks: Python (pandas, scikit-learn), TensorFlow, PyTorch, NLP/LLMs. Experience with Cloud Platforms: AWS (Redshift, Glue, Athena), Azure (Synapse, Data Factory), GCP (BigQuery, Dataflow). Familiarity with Data Governance, MDM, and Data Security frameworks. Understanding of modern architectures: data mesh, data fabric, lakehouse. Presales Skills Experience in preparing RFP/RFI responses, estimation models, and solutioning. Excellent client communication, proposal writing, and presentation skills. Ability to articulate ROI and business value in client conversations. General Skills 5-10 years of IT experience, with at least5+ years in solution architecture & presales . Strong leadership, analytical, and stakeholder management skills. Track record of winning Data/Analytics deals and enabling delivery success. Willingness to travel for client workshops and presales engagements.Education & Certifications Bachelor’s/Master’s in Computer Science, Engineering, or related field. Preferred Certifications: Cloud : AWS Data Analytics Specialty, Azure Data Engineer, GCP Professional Data Engineer. BI : Microsoft Power BI, Tableau Specialist. Architecture : TOGAF, Data Management certifications (DAMA/CDMP).

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