Senior Principal Data and AI Engineer- R&D IT

NXP Semiconductors; Bengaluru; On-site; INR 4,200,000 - 6,200,000; Full time

Job summary

NXP Semiconductors is seeking a Data & AI Engineering Lead to drive the design, implementation, and operation of scalable data and AI platforms for R&D. You will own the technical roadmap, guide platform architecture, and work closely with data engineers and scientists to turn complex data into actionable insights.

You will lead initiatives for lakehouse modernization, AWS-based data lake services, and production-grade GenAI workloads, ensuring security, reliability, and cost efficiency across

Qualifications

• 10+ years building and operating large-scale data platforms in enterprise environments.
• 2+ years delivering Generative and Agentic AI solutions including LLMs, RAG and MCP concepts.
• Experience with AWS-native data lake services including ETL orchestration, cataloging, governance, and secure access management.

Responsibilities

• Define and evolve the technical roadmap by translating R&D needs into prioritized backlog items with reliability, security, and cost improvements.
• Shape the architecture of the data and AI platform enabling scalable Lakehouse and GenAI workloads with governed self-service.
• Design, build, and operationalize production-grade Generative and Agentic AI solutions with reference architectures.
• Lead major initiatives such as lakehouse modernization and Databricks migrations across R&D platforms.
• Deliver large-scale ETL/ELT pipelines on AWS, Databricks, Delta Lake with robust schema management and data lifecycle practices.
• Implement observability, monitoring, cost control, and incident investigations to improve stability and performance.

Skills

Python

SQL

Leadership

Cloud architecture

GenAI & LLMs

MLOps

Education

Master's degree in Data Engineering, CS, or related field

Tools

Databricks

AWS Glue

S3

Delta Lake

Job description

Shape the future of AI-powered R&D at NXP Are you ready to build the next generation of data and & AI platforms at NXP? As a Data & AI Engineering Lead, you will play a pivotal role in accelerating and optimizing NXP’s New Product Introductions by designing, implementing, and operationalizing advanced, production-grade data and & AI solutions.

Your work will empower R&D teams with scalable platforms, intelligent assistants, and automated workflows that turn complex data into actionable insights. Working closely with data engineers, data scientists, solution architects, and domain experts, you will help define the future of data & AI capabilities within NXP R&D. You will take ownership of delivering robust, secure, and highly available data and & AI applications used across the engineering organization.

What you will do as a Data & AI Engineering Lead at NXP

Product Ownership & Backlog Contribution

Support the definition and evolution of the technical roadmap by translating R&D needs into well‑scoped, prioritized backlog items, providing technical input to prioritization, and ensuring reliability, security, cost, and operational improvements are explicitly represented.

Platform Architecture & Strategy

Shape the architecture of the R&D data and & AI platform in close collaboration with solution architects, defining technology choices, design patterns, and standards that enable scalable Lakehouse and GenAI workloads with governed self‑service, security, and long‑term maintainability.

AI & GenAI Enablement

Design, build, and operationalize production‑grade Predictive, Generative and Agentic & AI solutions, defining reference architectures for & AI workloads and collaborating with data scientists and domain experts to turn experimental use cases into robust, scalable, and secure production systems.

Large-Scale Platform & AI Initiatives

Lead major initiatives such as lakehouse modernization, migration from AWS Glue to Databricks, and the integration of & AI capabilities into existing platforms, enabling reusable data, features, and & AI components across R&D.

Data Engineering & Lakehouse Development

Design and deliver large-scale ETL/ELT pipelines using AWS, Databricks, Delta Lake, and distributed compute patterns, while ensuring consistent schema management, versioning, and data lifecycle practices across structured, semi‑structured, and unstructured data.

AI Operations, Reliability & Cost Control

Implement observability, monitoring, and evaluation for data and & AI systems, optimize performance and cost efficiency, and lead incident investigations to drive long‑term stability, reliability, and continuous improvement.

Engineering Excellence & Reusability

Develop reusable frameworks, templates, and libraries for data and & AI development, and promote best practices around versioning, evaluation, reproducibility, and lifecycle management.

Security, Governance & Compliance

Embed strong security, governance, and compliance controls across data and & AI solutions, defining access models, data classifications, and responsible & AI guardrails in partnership with Cyber Security and Legal teams.

Leadership & Mentoring

Mentor engineers through architectural guidance, design and code reviews, and elevate team maturity by driving technical standards and a culture of engineering excellence.

Operational Maturity

Continuously improve operational processes for data and & AI platforms by turning production learnings into automation, documentation, and platform enhancements.

What you bring

You can describe yourself as follows:

Education & Experience

Education: Master’s degree (or equivalent practical experience) in Data Engineering, Computer Science, Software Engineering, or a related technical field.

Data Engineering Experience: 10+ years of professional experience building and operating large-scale data platforms in enterprise environments with distributed data processing.

Generative & Agentic AI: 2+ years of hands‑on experience designing and delivering Generative and Agentic & AI solutions, including concepts such as LLMs, Retrieval‑Augmented Generation (RAG), and Model/Agent Control Patterns (e.g. MCP). Experience with Predictive & AI is a big plus.

AWS Data Lake Experience: Extensive experience with AWS‑native data lake services, including S3, Glue, Athena, and Lake Formation, covering ETL orchestration, cataloging, governance, retention, aggregation, backfilling, enrichment and secure access management.

Databricks & Migration Expertise: Deep hands‑on experience designing ETL pipelines on Databricks, including proven success migrating existing cloud‑native data lakes and workflows to the Databricks platform.

Delta Lake Expertise: Strong understanding of Delta Lake internals, including schema evolution, time travel, table optimization, and performance tuning at scale.

High‑Tech Domain Experience (Plus): Background and experience in high‑tech, R&D‑intensive environments, especially within semiconductor or automotive domains, is a strong plus.

Technical Skills Architecture & Design

Proven ability to define scalable data architectures, lakehouse patterns, and influence long‑term platform strategy.

Cloud & Automation: Strong experience with cloud‑native engineering on AWS. Hands‑on experience with Infrastructure-as-Code, CI/CD pipelines, and DevOps / MLOps best practices.

Programming: Advanced proficiency in Python and SQL, with a focus on building robust, maintainable, and reusable code.

GenAI Development: Experience working with various large language model families. Hands‑on knowledge of RAG pipelines, vector stores, orchestration frameworks, and agent‑based architectures. Familiarity with multimodal & AI solutions is a strong plus.

Data Quality & Governance: Strong command of data observability, lineage, metadata management, quality frameworks, and secure access patterns.

Performance & Cost Optimization: Expertise in cluster and workload tuning, orchestration strategies, storage optimization, and cost management in large‑scale data lake and lakehouse environments.

Professional Attributes

Mentorship & People Development: Proven experience mentoring and guiding engineers, fostering technical excellence, confidence, and continuous growth within the team.

Technical Leadership: Comfortable guiding engineers at all levels through architectural decisions, code reviews, and best practices.

Strategic Problem‑Solving: Able to own complex technical challenges and design scalable, long‑term solutions rather than short‑term fixes.

Stakeholder Mindset: Strong communicator who can translate complex technical concepts into business and R&D value.

Team‑Oriented: A collaborative engineer who raises the overall maturity of the team and contributes to a constructive, inclusive engineering culture.

Agile Ways of Working: Champions Agile and Scrum ways of working, enabling iterative delivery, effective backlog refinement, sprint planning, and strong cross‑functional collaboration.

More information about NXP in India... NXP Semiconductors N.V. (NASDAQ: NXPI) enables a smarter, safer, and more sustainable world through innovation. As the world leader in secure connectivity solutions for embedded applications, NXP is pushing boundaries in the automotive, industrial & IoT, mobile, and communication infrastructure markets. For more information, visit www.nxp.com Bright Minds. Bright Futures. We believe that a key component to growing our business is to develop our people. To enable you to grow your career at NXP, we offer online and offline learning opportunities to help you develop some of your core and professional skills. Commitment At NXP. We recognize NXP is a powerful change agent as we continue to deliver innovative solutions that advance a more sustainable future. We remain steadfast in our commitment to sustainability and making measurable year‑on‑year progress. Also, we aim to create an inclusive work environment and we will not tolerate racism, discrimination or harassment of any kind. We have programs in place focused on diversity, inclusion and equality. Thank you for considering a career at NXP.

Thank you for your interest in supporting our recruitment efforts. Any candidate profiles or resume submitted without a prior written agreement or explicit request from our Talent Acquisition team will be considered unsolicited. Such submissions will be deemed free of any obligations, and no fees will be paid by NXP or any of its affiliates, subsidiaries, or divisions – regardless of whether the candidate is hired, either coincidentally or otherwise.