Senior Solution Architect

We need to output HTML fragment with sections: About the role? The posting includes description. We need headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections when there is real specific content. We have: - About the role: Could be the introductory paragraph: "Senior Solution Architect (Data & AI Solution Specialist) Must Have Technical/Functional Skills A senior Solution architecture specialist focused on designing and championing cloud-native Data & AI solutions for Banking, Financial services and Insurance clients. This role translates complex business requirements into winning technical solutions – leveraging modern data & AI platforms and AI/ML services on cloud – and ensures proposals are compelling, feasible, and outcome-oriented. The Data & AI Solution Specialist works closely with Data & AI Practice, Onsite teams and customer teams and client stakeholders to drive deal success and leading delivery teams for execution." We can put that under

About the role

with

. - Responsibilities: The "Roles & Responsibilities" section includes many bullet points. We'll list them as

• . - Requirements / Qualifications / Skills: The "Must Have Technical/Functional Skills" and "Must Have Skills" list. Could combine into Requirements or Skills. We need to decide. The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Skills). We can include Requirements and Skills separate if content distinct. We have must-have skills list (experience, platforms). Also there is "Must Have Technical/Functional Skills" which is similar. We could put under Requirements (experience) and Skills (technologies). But we must not create thin sections. Perhaps combine into one "Requirements" covering experience and skills. Or we could have "Requirements" for experience and "Skills" for technical platforms. Let's see content: Must Have Technical/Functional Skills paragraph then "Must Have Skills" list with bullet points. So we could have:

  Requirements

  15+ years of experience in data architecture, data engineering, and analytics platforms; strong consulting experience in large BFSI transformation programs; hands-on experience with preparation for Data Analytics Solution architecture, client presentations and PoC development; excellent stakeholder communication and leadership skills; experience working in regulated environments with data governance and compliance requirements.

  Skills

  • 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
  • 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 with preparation for Data Analytics Solution architecture, client presentations and Proof of concepts development (maybe duplicate)
  ... etc. But we need to avoid duplication. We'll extract unique items. Also we have Salary Range: $160,000-$180,000 a year. So we need Pay section. No Benefits or Schedule mentioned, so omit those. We must not include boilerplate like EEO etc. Not present. We must not repeat job title as heading. We must not include Job ID etc. Now produce HTML fragment. Structure:

  About the role

  ...

  Responsibilities

  • ...
  ...

  Requirements

  ...

  Skills

  • ...
  ...

  Pay

  Salary Range- $160,000-$180,000 a year

  Make sure to preserve all substantive information. Let's extract details. About the role paragraph: combine first two sentences? Actually the posting: "Job Description Senior Solution Architect (Data & AI Solution Specialist) Must Have Technical/Functional Skills A senior Solution architecture specialist focused on designing and championing cloud-native Data & AI solutions for Banking, Financial services and Insurance clients. This role translates complex business requirements into winning technical solutions – leveraging modern data & AI platforms and AI/ML services on cloud – and ensures proposals are compelling, feasible, and outcome-oriented. The Data & AI Solution Specialist works closely with Data & AI Practice, Onsite teams and customer teams and client stakeholders to drive deal success and leading delivery teams for execution." We'll output that as a paragraph. Responsibilities: list each bullet from "Roles & Responsibilities". Let's extract: - 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. - 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-concept, 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 Note there is some repetition: "Design and implement AI and Gen AI solution for data value chain" appears twice. We'll keep once. Now Requirements: from "Must Have Technical/Functional Skills" paragraph and maybe other experience statements. Paragraph: "A senior Solution architecture specialist focused on designing and championing cloud-native Data & AI solutions for Banking, Financial services and Insurance clients. This role translates complex business requirements into winning technical solutions – leveraging modern data & AI platforms and AI/ML services on cloud – and ensures proposals are compelling, feasible, and outcome-oriented. The Data & AI Solution Specialist works closely with Data & AI Practice, Onsite teams and customer teams and client stakeholders to drive deal success and leading delivery teams for execution." But that's more about role. The Must Have Technical/Functional Skills maybe just that paragraph? Actually the heading "Must Have Technical/Functional Skills" then the paragraph. Then "Must Have Skills" list. Thus Requirements could be the paragraph about experience: "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 more of AWS, GCP, AzureDeep experience in Snowflake or Databricks with usage of open source extensions like Iceberg, dbtExperience 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" We need to parse that into a coherent paragraph. Let's rewrite: - 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. - 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. We can put that as a
  under Requirements, but the instruction says use
  • for any list of duties/requirements/benefits. So we can make Requirements a list. Similarly Skills could be the list of specific technologies: maybe we already covered many. But to avoid duplication, we could treat Requirements as experience and Skills as technical platforms. However the Must Have Skills list includes many technical items overlapping with experience list. Might be better to have one Requirements section covering both experience and skills, and omit Skills section to avoid thin duplication. But we need to follow instruction: prefer a few substantive sections over many thin ones. So we can combine into Requirements only, and not have Skills. Thus sections: About the role, Responsibilities, Requirements, Pay. Check if any Benefits or Schedule: none. Now produce HTML. Make sure to not include extra whitespace? It's fine. Let's craft. About the role paragraph: combine the description. I'll write:

    Senior Solution Architect (Data & AI Solution Specialist) – a senior solution architecture specialist focused on designing and championing cloud-native Data & AI solutions for Banking, Financial services and Insurance clients. This role translates complex business requirements into winning technical solutions – leveraging modern