Dataweave- Technical Architect

Role- technical Architect

Location- Bengaluru (Bannerghatta Road)

Work Mode- Hybrid (3 days work from office)

DataWeave provides Retailers and Brands with Competitive Intelligence as a Service, enabling data-driven decisions that directly impact revenue. Powered by AI, we aggregate and analyze billions of publicly available data points to help businesses develop smarter competitive strategies. Our Products team builds data products at scale — timely, actionable, and deeply consumable — with a relentless focus on customer value.

We are looking for a seasoned Technical Architect to lead engineering excellence across our web application stack. This is a hands-on architectural leadership role, you will own end-to-end technical quality, drive scalable SaaS product design, champion AI-native development practices, and enable developer productivity through intelligent tooling and automation. You will work closely with engineering leadership, product teams, and cross-functional stakeholders to deliver high-impact solutions in a fast-paced, customer-obsessed environment.

• Own architectural decisions for web applications, APIs, and microservices, in consultation with engineering leadership, ensuring scalability, reliability, and maintainability.
• Drive end-to-end technical quality: code standards, design reviews, NFR (non-functional requirements) definition, and realization from architecture through deployment.
• Lead architecture definition for SaaS products, including multi-tenancy, extensibility, and platform scalability, ensuring alignment with long-term product roadmap.
• Identify and mitigate technical risks early; escalate proactively to ensure sprint and delivery commitments are protected.
• Lead the design and scaling of SaaS applications, driving best practices around API design, service decomposition, data modelling, and platform architecture.
• Build and scale large-scale, data-driven products typical of analytics and competitive intelligence domains, with a focus on performance, reliability, and domain-specific use case delivery.
• Ensure production readiness: capacity planning, performance tuning, observability, and incident response readiness for all solutions delivered.

• Embed, drive adoption AI-native practices across the full engineering lifecycle, from technical design and solution architecture to code generation, review, quality assurance and deployment.
• Champion the use of AI-assisted development tools (e.g., Claude, Cursor, GitHub Copilot) as standard practice within the team, not optional augmentation.
• Exposure to Designing and building functional agents and developer productivity agents to automate repetitive engineering tasks,  including health checks, auto-healing workflows, and support use cases for platform components.

• 10+ years of core software development experience, with significant tenure in product-based companies.
• Proven track record leading engineering teams in dynamic, fast-paced, customer-focused environments with rapid release cycles.
• 5+ years of experience architecting server-side web applications, REST APIs, and microservices at scale.
• Demonstrated experience building and scaling SaaS products, including multi-tenancy, subscription models, and platform extensibility.
• Experience building large-scale, data-driven products in analytics or competitive intelligence domains, domain-specific data apps, insight platforms, or similar.

• Hands-on, production-grade experience with AI-assisted development tools — Claude, Cursor, GitHub Copilot, or equivalent — across design, development, and review workflows.
• Proven experience building or operating developer productivity agents for recurring engineering tasks: health checks, auto-healing, platform support automation.
• Familiarity with agent frameworks, prompt engineering, LLM orchestration, and integrating AI tooling into CI/CD and developer workflows.

• Languages: Strong proficiency in Python and related frameworks.
• Databases: Strong SQL, NoSQL exposure - including index management, partitioning, system catalogs, and SQL query tuning.
• DevOps: Docker, Kubernetes  
• Data: Experience with data pipelines, distributed message queues, and stream processing.
• Cloud: Experience creating and managing cloud infrastructure for application deployment and scale.
• Documentation: Proficient in producing Architecture Views, Technology Architecture Blueprints, and Design Specifications.

• Inclusive, roll-up-your-sleeves work ethic willing to participate in daily workloads when it matters.
• Eagerness to learn, experiment, and adopt new technologies especially at the intersection of AI and software engineering.
• Clear, structured communicator, able to translate complex technical decisions for both engineering and business stakeholders.
• A builder's mindset: you think in systems, care about outcomes, and take pride in what ships.