Data Architect

TechBlocks; Hyderabad; On-site; INR 600,000 - 900,000; Full time

Job summary

TechBlocks seeks an accomplished data architecture leader to design and implement scalable, end-to-end data platforms. You will model complex financial datasets and build semantic data models with ontologies and SHACL validation to enable robust analytics and governance.

You will collaborate closely with engineering teams, contributing hands-on to production code and guiding architectural decisions. Proficiency across AWS/Azure/GCP and knowledge graph technologies is essential for this role.

Qualifications

• 15+ years building production systems in large-scale environments.
• Designing scalable data architecture for enterprise systems.
• Hands-on experience in semantic data engineering and knowledge graphs.
• Strong coding mindset with close-to-production execution.
• Experience with end-to-end financial workflows and data governance.

Responsibilities

• Design and implement scalable, end-to-end data architectures across ingestion, pipelines, data platforms, data mesh, and downstream consumption layers.
• Lead data modelling efforts across conceptual, logical, and physical levels for large datasets and reporting needs.
• Create and maintain semantic/canonical models using ontologies and SHACL validation, building enterprise knowledge graphs.
• Act as a technical partner to engineering teams, guiding architecture and delivery quality.
• Review and improve production code, collaborating with senior engineers on complex challenges.
• Integrate AI Agents and MCP-based capabilities with enterprise data platforms for secure, governed access.
• Design agent-ready data and context architectures with strong security, observability, and reliability controls.
• Demonstrate practical expertise with cloud platforms (AWS, Azure, GCP) for multi-tenant, cost-performance optimized solutions.

Skills

15+ years experience

Data architecture design

Comprehensive data modelling

Semantic data engineering

Ontology development

RDF/OWL

SPARQL

SHACL

Knowledge graphs

End-to-end financial workflows

MCP integrations

Cloud platforms (AWS/Azure/GCP)

Agentic solutions

Tools

Erwin

RStudio

Job description

Responsibilities

• Design and implement scalable, end-to-end data architectures encompassing source system ingestion, integration pipelines, cloud-native data platforms, data mesh and downstream analytical and operational consumption layers, ensuring robustness, scalability, and security.
• Lead comprehensive data modelling efforts across conceptual, logical, and physical layers, applying best practices in normalized (3NF) and dimensional modelling to support complex, high-volume financial datasets and enable effective reporting and analytics.
• Create and maintain semantic/canonical models using ontologies and validate data integrity via SHACL shapes to build enterprise knowledge graphs, establishing consistent terminology, enforcing data quality constraints, enhancing data interoperability.
• Serve as a trusted, domain-aware technical partner to engineering teams to providing guidance and hands-on support to ensure architectural integrity and delivery excellence.
• Maintain hands-on involvement in reviewing, writing, and improving production code; collaborate with senior engineers to solve complex technical challenges and ensure high-quality deliverables.
• Integrate AI Agents and MCP-based capabilities with enterprise data platforms, enabling secure, governed access to data, tools, and services through scalable and production-ready patterns.
• Design agent-ready data and context architectures leveraging knowledge graphs, semantic models, metadata, and APIs, with strong controls for security, observability, auditability, reliability, and graceful failure.
• Demonstrate practical expertise with cloud platforms (AWS, Azure, GCP), leveraging managed services, multi-tenant architectures, and balancing cost-performance trade-offs effectively.

What are we looking for

• 15+ years building and operating production systems, with increasing depth of expertise at each level.
• Proven hands-on experience in designing and implementing scalable data architecture and comprehensive data modelling (conceptual, logical, and physical) for large-scale enterprise systems using tools like Erwin/RStudio.
• Strong engineering background with the ability and willingness to remain close to the code, implementation, and production environment.
• Strong hands-on expertise in semantic data engineering, ontology development, RDF/OWL, SPARQL, SHACL, and knowledge graph technologies, with experience designing scalable semantic models, validation frameworks, and graph-based solutions.
• Possess strong knowledge of end-to-end workflows relevant to financial domains (e.g., trade lifecycle, processing, reporting, reconciliation), and design data architectures that optimize data movement, quality, lineage throughout and operational resilience throughout these workflows.
• In-depth knowledge about Agentic solutions and MCP-based integrations, with a strong understanding of agentic architectures, enterprise data access, tool integration, security, governance, observability, and production reliability.
• Proven experience building large-scale, distributed, data-intensive, and event-driven systems with cloud-native architectures preferably within financial services or another highly regulated industry.

Leadership Influence

• Demonstrated ability to lead through technical credibility hands-on contribution.
• Strong communication skills, with the ability to engage effectively with engineers, engineering managers, product leaders, architects, and senior segment leadership.
• Able to operate effectively across multiple delivery pods, balancing strategic architectural direction with day-to-day engineering realities.
• A strong sense of ownership for outcomes, with the ability to stay engaged from architecture through implementation and production operation.