Senior Solution Architect

New York, NY | 10 - 18 years of experience Senior Solution Architect (Data & AI Solution Specialist) Must Have Technical/Functional Skills 15+ years of experience in data architecture, data engineering, and analytics platforms Experience across AWS, GCP, Azure, Snowflake, Databricks, Iceberg, dbt and open source tech based data services with depth expectations as below: Deep experience on one or more of AWS, GCP, Azure Deep experience in Snowflake or Databricks with usage of open source extensions like Iceberg, dbt Experience in open-source technologies based Enterprise Data architecture Strong consulting experience in large BFSI transformation programs Hands on experience with preparation for Data Analytics Solution architecture, client presentations and Proof of concepts development Design and implement AI and Gen AI solution for data value chain Very strong understanding and experience of Data products, data mesh and Medallion Architecture implementation Strong background in data integration, reporting, and big data ecosystems Experience working in regulated environments with data governance and compliance requirements Excellent stakeholder communication and leadership skills Responsibilities Client Consulting & Opportunity Shaping: Lead workshops and consultations with client business and IT stakeholders to uncover needs in areas like data modernization, advanced analytics, AI/ML, and regulatory compliance. Translate business objectives (e.g. enhanced customer insights, automation of processes, risk analytics) into well-defined Data & AI use cases and solution approaches. Solution Architecture & Design: Develop end-to-end cloud-native data & AI architectures – spanning data ingestion, storage (data lakes/warehouses/data integration, transformation and Data products), processing pipelines, analytics dashboards, and machine learning/AI platforms. Ensure designs meet non-functional requirements (scalability, security, resilience, performance) and align with BFSI regulatory and security standards. End-to-End System Design: Mapping out the precise technical lifecycle of data, including pipeline orchestration, data warehousing, and API integrations Technology Selection: Vetting and selecting the optimal tech stack, such as specific cloud services (e.g., AWS, Azure, GCP), data warehouses (e.g., Snowflake, BigQuery), or streaming engines (e.g., Kafka) Data Modeling: Designing detailed conceptual, logical, and physical data models (like Data Vaults or Star Schemas) to ensure optimal query performance and data integrity. Security & Governance: Baking strict data privacy, compliance (e.g. GDPR, HIPAA), and access control frameworks directly into the architecture. Consulting Leadership: Own the technical solution in Consulting opportunities and RFP responses. Write and present the solution overview, methodology, delivery plan, and value proposition. Quantify business benefits (e.g. faster time-to-insight, cost savings through cloud, improved compliance through better data governance) and contribute to pricing and effort estimates. Ensure proposals clearly address client pain points and differentiate TCS’s Data & AI capabilities. Demonstrations & Proof of Concept (PoC): Create and deliver impactful demos, proofs-of-concepts, and prototypes using cloud data platforms (Data integration, Transformation and Data products) and AI services to validate solution feasibility and value. Tailor demo scenarios to BFSI use cases (like fraud detection, customer 360 analytics, regulatory reporting) to build client confidence. Collaboration & Handover: Work closely with internal teams – sales, delivery managers, domain consultants, and cloud partners – to ensure proposed solutions are deliverable and aligned with available capabilities. Assist in a smooth transition from sales to delivery, briefing delivery teams on the designed solution, architecture decisions, and client expectations. Provide early-stage support to resolve any design challenges. Thought Leadership & Best Practices: Contribute to the development of re-usable Data & AI accelerators, reference architectures, and best practice guides. Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients. Architect and implement scalable solutions using Snowflake and Databricks on AWS, GCP and Azure platforms. Design and implement AI and Gen AI solution for data value chain. Design data integration pipelines (batch, real-time, big data) and analytics platforms. Enable enterprise reporting and BI solutions for regulatory and business needs. Define and implement data governance, quality, metadata, and lineage frameworks. Act as a trusted advisor to senior business and IT stakeholders. Participate in Data Analytics Architecture and Delivery reviews and provide recommendations. Mentor junior solution architects and stay up to date with emerging cloud data technologies (e.g. Data Lakehouse, DataOps / MLOps, generative AI) to continuously enhance proposal quality. Mentor teams and contribute to solutioning and pre-sales activities. #J-18808-Ljbffr