Principal Data Architect

Overview

Principal Data Architect at Thoughtworks, leading the design and architecture of data programs and guiding delivery teams and clients on data strategy, engineering, machine learning and Agentic AI.

What you'll do

• Lead complex data programs, navigating architectural concerns and enabling delivery teams to deliver to accepted standards within time and budget.
• Provide client-facing technical leadership and guidance on data engineering, machine learning and Agentic AI to bring clients' data strategy to life.
• Interact with client enterprise architecture counterparts and lead the delivery, alignment and sign-off of key architectural decisions, trade-offs and ways of working.
• Communicate trade-offs of technology choices to stakeholders with varying levels of technical expertise, covering high-level and low-level details.
• Map business capabilities, business processes, information flow and technology solutions to business outcomes and concrete KPIs aligned with OKRs and KRAs for a domain or industry.
• Be responsible for the technical design of data governance, data security and data privacy to fulfill compliance requirements, and detect and mitigate threats, vulnerabilities and unintended consequences of data use.
• Incorporate data quality frameworks and processes to meet strategy requirements and acceptance criteria.
• Collaborate with sales and pre-sales to clarify requirements and design viable solutions, and envision and articulate solution architecture artifacts.
• Represent Thoughtworks in online and offline forums, including events and conferences.
• Coach, mentor and guide delivery teams on architectural decisions to deliver against solution agreements.

What you'll need

• Multi-cloud experience across major hyperscalers (AWS, Azure, GCP) with relevant certifications.
• Deep expertise in big data technologies, modern lakehouses and platforms such as Databricks, Snowflake and Fabric.
• Proven track record in end-to-end building, performance tuning and monitoring of enterprise data platforms, including real-time streaming architectures (e.g., Apache Kafka, Spark Streaming).
• Strong background in overall system architecture design, data warehouse design and data modeling (Dimensional, Data Vault), data mesh, data as a product, data governance, data quality and lineage, and trade-off analysis for technology selection.
• Comprehensive experience in AI/ML solutions, orchestrating MLOps pipelines, managing vector databases (e.g., Pinecone, Milvus, Chroma) and productionizing AI models at scale.
• Strong hands-on PySpark development skills combined with DataOps best practices, Infrastructure as Code (Terraform/CloudFormation) and automated CI/CD deployment pipelines for data platforms.
• Proficiency in applying AI-assisted and agentic coding workflows to accelerate data pipeline engineering, automated data transformations and system development.
• Stakeholder management skills to liaise between clients and key stakeholders, ensuring buy-in and trust.
• Resilience in ambiguous situations and the ability to approach challenges from multiple perspectives.
• Willingness to take on and skillfully manage risks and conflicts.
• Ability to coach, mentor and motivate others and influence teammates toward positive action and accountability.
• Advocacy for technical excellence while being open to change, and strong relationship-building skills.

Nice to have

• Certifications in cloud, data and AI platforms (Databricks, Snowflake, Azure, AWS, Claude).

Details

• Location: Bangalore, India.
• Work mode: Hybrid.