Principle Data Engineer

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Job Description

The Future Begins Here

At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet.

Bengaluru, the city, which is India’s epicenter of Innovation, has been selected to be home to Takeda’s recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.  

At Takeda’s ICC we Unite in Diversity

Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team.

The Opportunity:

As a Principal Data Engineer for Data & AI Architecture, you will define and own the enterprise data, GenAI, and agentic architecture that enables analytics, AI products, and intelligent automation at scale.
This role is accountable for translating business and AI strategy into reference architectures, proof-of-concepts (POCs), and production-grade platforms, ensuring data quality, governance, security, and AI readiness across the organization.

You will operate at the intersection of traditional data engineering, modern lakehouse platforms, GenAI enablement, and agentic orchestration, guiding teams from experimentation to enterprise adoption.

Accountabilities

• Own and evolve the enterprise data and AI architecture, including standards, principles, and reference architectures for analytics, GenAI, and agentic systems.
• Define GenAI-ready data architectures, including datasets for LLM consumption, feature stores, vector embeddings, semantic layers, and metadata-rich knowledge assets.
• Lead architecture and delivery of POCs and MVPs for GenAI and agentic use cases, validating feasibility, scalability, cost, and security prior to production rollout.
• Design scalable solution architectures integrating structured, semi-structured, and unstructured data to support analytics, LLMs, and autonomous agents.
• Lead enterprise data modeling within Databricks and cloud platforms, including analytical models, domain-oriented models, and AI feature models.
• Translate business, analytics, and AI use cases into conceptual, logical, and physical data models optimized for performance and AI consumption.
• Partner with business architects, data stewards, analytics engineers, and AI/ML teams to align domain models with GenAI and agentic workflows.
• Convert logical models into physical implementations and guide data engineering teams on ELT, streaming, orchestration, and automation patterns.
• Evaluate and recommend data, GenAI, and AI orchestration platforms, including lakehouse technologies, vector databases, LLM frameworks, and agentic runtimes.
• Collaborate with BI, Analytics, and AI teams to design reusable semantic models, governed datasets, and lineage-aware AI inputs.
• Define and govern enterprise data, AI, and GenAI design standards, tools, and best practices across the SDLC.
• Establish metadata, lineage, and observability strategies that support trust, explainability, and responsible AI.
• Define agentic and GenAI design patterns, including Retrieval-Augmented Generation (RAG), tool-calling, autonomous workflows, and human-in-the-loop controls.
• Drive multi-phase data and AI roadmaps, balancing innovation, platform stability, and technical debt reduction.
• Provide architectural guidance that mitigates data, security, cost, and AI risks at enterprise scale.
• Identify and implement AI-assisted automation across data engineering and analytics workflows.
• Design and optimize pipelines for ingestion, transformation, feature engineering, and AI data delivery using SQL, Python, and cloud-native services.
• Produce high-quality architecture artifacts, data models, POC documentation, and AI solution blueprints.

Skills and Qualifications

• Bachelor’s degree or higher in Computer Science or a related discipline, or equivalent experience.
• 7+ years of experience in data architecture and platform design for enterprise analytics systems.
• Strong experience designing lakehouse and cloud-native data platforms supporting both analytics and AI workloads.
• Proven ability to lead GenAI and agentic POCs from problem framing through production recommendations.
• Advanced data modeling expertise across analytical, domain-oriented, and AI feature models.
• Deep understanding of ELT, orchestration, data quality, observability, and scalable pipeline design.
• Strong SQL expertise and working knowledge of Python for data and AI workflows.
• Experience working within AWS-based data and AI ecosystems.
• Ability to operate effectively in fast-moving environments with ambiguity, rapidly iterating on POCs and architectural decisions.
• Strong communication and stakeholder management skills across business, engineering, and AI teams.
• Self-directed, outcome-oriented, and comfortable owning architecture decisions end-to-end.

Preferred But Not Required

• Hands-on experience with Databricks Lakehouse and Spark-based processing.
• Exposure to GenAI architectures, including LLMs, Retrieval-Augmented Generation (RAG),embeddings, vector databases, and prompt pipelines.
• Experience designing or integrating agentic workflows, tool-calling frameworks, or AI orchestration layers.
• Familiarity with Informatica or other enterprise ELT platforms.
• Experience using GitHub and CI/CD practices for data and AI assets.
• Working knowledge of ML lifecycle concepts, feature stores, and model observability.
• Experience delivering POCs that transition into enterprise-grade production systems.

WHAT TAKEDA CAN OFFER YOU:

Takeda is a globally recognized Top Employer, investing heavily in people, learning, and innovation.  Opportunity to lead GenAI and agentic architecture initiatives that move beyond experimentation into real business impact.  Access to advanced platforms, continuous upskilling, and a collaborative ecosystem at the ICC in Bengaluru.

BENEFITS:

It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are:

• Competitive Salary + Performance Annual Bonus
• Flexible work environment, including hybrid working
• Comprehensive Healthcare Insurance Plans for self, spouse, and children
• Group Term Life Insurance and Group Accident Insurance programs
• Health & Wellness programs including annual health screening, weekly health sessions for employees.
• Employee Assistance Program
• 5 days of leave every year for Voluntary Service in additional to Humanitarian Leaves
• Broad Variety of learning platforms 
• Diversity, Equity, and Inclusion Programs
• No Meeting Days
• Reimbursements – Home Internet & Mobile Phone
• Employee Referral Program
• Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 calendar days)

ABOUT ICC IN TAKEDA:

• Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day.
• As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.

#Li-Hybrid

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