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Western Digital

Principal Engineer, Data Analytics Engineering (Data Engineering , GenAI , Python , SQL)

Posted 5 Days Ago
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In-Office
Bengaluru, Bengaluru Urban, Karnataka
Expert/Leader
In-Office
Bengaluru, Bengaluru Urban, Karnataka
Expert/Leader
Lead architecture and delivery of scalable AI/GenAI and data engineering solutions on AWS. Build ETL/ELT pipelines, deploy LLM-based GenAI applications (RAG, copilots, agents), define cloud-native architectures, establish MLOps and governance, evaluate emerging tech, and mentor engineering teams.
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Company Description

The future. It’s on you. You & Western Digital.

We’ve been storing the world’s data for more than 50 years. Once, it was the most important thing we could do for data. Now we’re helping the world capture, preserve, access and transform data in a way only we can.

The most game-changing companies, consumers, professionals, and governments come to us for the technologies and solutions they need to capture, preserve, access, and transform their data.

But we can’t do it alone. Today’s exceptional data challenges require your exceptional skills. It’s You & Us. Together, we’re the next big thing in data. 
 
Western Digital® data-centric solutions are found under the G-Technology™, HGST, SanDisk®, Tegile™, Upthere™, and WD® brands.

Job Description

Position: Principal AI Engineer (Data Engineering & GenAI)

We are seeking a Principal AI Engineer with deep expertise in data engineering, Generative AI (GenAI), and AWS cloud platforms to architect and lead scalable AI-driven solutions that address complex business and technology challenges.

Key Responsibilities

  • AI Platform Architecture: Design and implement scalable AI/ML and GenAI solutions on AWS using modern data engineering frameworks and best practices.
  • Data Engineering Leadership: Drive the development of robust data pipelines, ETL/ELT frameworks, and data models that support AI/ML and analytics use cases at scale.
  • Generative AI Solutions: Lead the exploration, prototyping, and deployment of GenAI applications (LLM-based copilots, RAG pipelines, autonomous agents) across enterprise scenarios.
  • Technology Strategy: Evaluate and adopt emerging technologies to strengthen AI and data engineering efficiency and capabilities.
  • Cloud & Infrastructure: Define and implement cloud-native architectures using AWS services (S3, Glue, Redshift, EMR, Lambda, SageMaker, Bedrock, EKS).
  • Collaboration & Influence: Partner with data scientists, product managers, and business stakeholders to translate business needs into scalable technical solutions.
  • Best Practices & Governance: Establish coding standards, DevOps/MLOps practices, and enforce data governance and security controls for AI workloads.
  • Mentorship & Leadership: Guide and mentor engineers and data professionals, fostering innovation, technical excellence, and best practices.

Qualifications

Basic Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or related field.
  • Advance experience in data engineering, AI/ML systems, and cloud computing.
  • Proven expertise with AWS cloud ecosystem (S3, Glue, Redshift, EMR, Lambda, SageMaker, Bedrock) and Databricks.
  • Hands-on experience with Generative AI models (LLMs, diffusion models), frameworks (LangChain, Hugging Face, OpenAI/Anthropic APIs), and RAG implementations.
  • Strong programming skills in Python, SQL, and at least one compiled language (Java, Scala, or Go).
  • Experience with modern data engineering tools and pipelines (Airflow, Spark, Kafka, dbt, Snowflake).
  • Excellent problem-solving skills with experience in architecture design and stakeholder communication.

Preferred Qualifications

  • Experience with vector and graph databases (e.g., Pinecone, Weaviate, pgvector, Neo4j).
  • Working knowledge of MCP (Model Context Protocol) for orchestrating and managing AI agent workflows.
  • Familiarity with containerization and orchestration (Docker, Kubernetes, EKS)
  • Knowledge of MLOps/LLMOps practices and CI/CD pipelines for AI workloads (e.g., MLflow, Kubeflow, LangSmith).
  • Strong understanding of data security, compliance, and governance in cloud and AI systems.

Additional Information

Because Western Digital thrives on the power of diversity and is committed to an inclusive environment where every individual can thrive through a sense of belonging, respect, and contribution, we are committed to giving every qualified applicant and employee an equal opportunity.  Western Digital does not discriminate against any applicant or employee based on their protected class status and complies with all federal and state laws against discrimination, harassment, and retaliation, as well as the laws and regulations set forth in the "Equal Employment Opportunity is the Law" poster.

WD thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

WD is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at [email protected] to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Notice To Candidates: Please be aware that WD and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately to WD Ethics Helpline or email [email protected].

Top Skills

Python,Sql,Java,Scala,Go,Aws S3,Aws Glue,Aws Redshift,Aws Emr,Aws Lambda,Aws Sagemaker,Aws Bedrock,Eks,Databricks,Langchain,Hugging Face,Openai Api,Anthropic Api,Rag,Llms,Diffusion Models,Airflow,Spark,Kafka,Dbt,Snowflake,Pinecone,Weaviate,Pgvector,Neo4J,Mcp,Docker,Kubernetes,Mlflow,Kubeflow,Langsmith,Mlops,Llmops

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