Solution Architect Specialist

Job description

Req ID: 57431 Job Function: Engineering Posting Start Date: 12/08/2026 Posting End Date: 17/08/2026 Division: Digital Job Location: IND-Bengaluru-RMZ Ecoworld Advertised Salary: Competitive **Recruiter: Seema Shivakumar** **Hiring Manager: Arnab Bose** **Career Grade: D** ## **About the role** We are looking for a highly skilled Data Solution Architect Specialist to lead the strategy, design, and delivery of cloud-based data solutions with a strong focus on Google Cloud Platform (GCP). In this role, you will own the end to end technical architecture—spanning discovery, feasibility analysis, solution design, data modelling, integration patterns, and guiding technical teams through implementation. You will partner closely with engineering, analytics, product, and architecture teams to translate complex business needs into scalable, secure, and high performing data platforms and pipelines. This role suits someone who is hands on, technically deep in cloud data architecture, and comfortable providing leadership across both design governance and delivery execution. ## **What you’ll be doing** 1. Architecture & Solution Design - Lead the design of end-to-end cloud data architectures primarily on GCP (BigQuery, Cloud Storage, Pub/Sub, Dataflow, Cloud Composer, Looker, etc.). - Architect scalable data ingestion, transformation, and consumption layers following modern data engineering principles. - Define data flow diagrams, logical/physical data models, and integration patterns across systems and platforms. - Develop and maintain solution blueprints, architectural standards, and reusable design assets. - Develop logical and physical data models, star/snowflake schemas, semantic layers, and domain-aligned data structures. - Define canonical data models, source-to-target mappings, and translation logic across diverse datasets and systems. 2. Data Transformation & Data Translation - Architect scalable ELT/ETL transformation patterns across batch and streaming pipelines. - Design and document transformation logic including cleansing, harmonisation, enrichment, and derivation rules. - Establish reusable transformation frameworks using tools such as Dataflow, Dataproc, Composer, SQL, dbt, or equivalent. - Ensure transparent, governed, and version-controlled translation of business rules into technical logic. 3. Discovery, Feasibility & Technical Analysis - Work with business and technical stakeholders to run discovery workshops, identify requirements, constraints, and success criteria. - Conduct feasibility assessments, evaluate architectural options, and recommend optimal design approaches. - Perform technology assessments, data profiling exercises, and gap analysis across data sources, pipelines, and platforms. 4. Technical Leadership & Governance - Provide technical leadership to engineering and data teams throughout the delivery lifecycle. - Review solution designs, code, pipelines, SQL transformations, and architecture deliverables and architecture decisions to ensure alignment with compliance and quality. - Champion data security, compliance, governance, and privacy standards across all designs. - Act as the primary architecture authority for assigned data programmes and projects. 5. End-to-End Solution Delivery - Design complete source-to-consumption data flows, including ingestion staging transformation warehouse serving. - Oversee the delivery of all architectural components from design through deployment. - Collaborate with engineering to implement high-quality, resilient, and cost-optimised cloud data solutions. - Ensure solutions meet functional and non functional requirements (scalability, performance, reliability, SLAs). - Support productionisation activities, testing strategies, and operational readiness. 6. Cross Functional Collaboration - Act as a bridge between data stakeholders—engineering, analytics, product owners, platform teams, and enterprise architects. - Translate business objectives into clear technical specifications and architectural deliverables. - Work closely with platform and security teams to ensure alignment with enterprise architecture frameworks. 7. Discovery, Feasibility & Stakeholder Engagement - Lead discovery workshops to gather requirements, map data sources, assess complexity, and scope solutions. - Conduct feasibility studies evaluating architectural options, performance considerations, and cost implications. - Translate business requirements into structured architectural artefacts, models, and technical specifications. - Communicate complex data designs clearly to both technical and non technical audiences. ## **Essential Skills / Experience** Technical Expertise - 14+ years of experience in data architecture, solution design, or advanced data engineering roles. - Deep hands on expertise with Google Cloud Platform (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Run, Cloud Storage, Cloud Composer). - Strong proficiency in: o Data modelling (logical & physical models, dimensional modelling, CDM/3NF, MDM structures) o ETL/ELT architecture and data integration patterns o Streaming and batch data pipelines o APIs, microservices, and integration architectures - Understanding of data governance, data cataloguing, lineage, and metadata-driven frameworks. - Experience designing secure, compliant, and governed cloud data environments (IAM, VPC, KMS, etc.). Architecture & Leadership Skills - Proven ability to lead architecture design, solution governance, and technical steering. - Strong documentation and diagramming capabilities (UML, BPMN, ArchiMate, ERD tools). - Strong experience designing end-to-end DWH and transformation pipelines in cloud environments. - Excellent communication and stakeholder management skills. - Expertise in preparing architecture diagrams, data models, and detailed transformation documents. - Ability to simplify complex technical concepts for non technical audien