Staff Engineer, Data Analytics Engineering at Western Digital

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

29 Sep, 26

Salary

0.0

Posted On

01 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Spark, AWS, Generative AI, LLMs, RAG, Vector Databases, Kafka, Airflow, Docker, Kubernetes, CI/CD, MLOps, Data Engineering, Data Pipelines

Industry

Computer Hardware Manufacturing

Description

Company Description WD is building the infrastructure behind the AI-driven data economy. As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time. That’s where we come in. We combine deep engineering expertise with global-scale manufacturing to deliver the storage systems that make AI possible, powering hyperscale data centers, cloud platforms, and enterprise infrastructure worldwide. This isn’t theoretical work. It’s real systems, at real scale, people solving some of the hardest challenges in technology today. We’re looking for people who want to build, solve, and operate at that level. Join us and let’s shape the future of data. Job Description Job Title: Data Engineer & GenAI Engineer We are seeking a Data Engineer & GenAI Engineer with strong expertise in modern data platforms, cloud-native architectures, big data technologies, and Generative AI solutions to design and deliver scalable data products, AI-driven applications, and intelligent analytics platforms that power enterprise innovation. Key Responsibilities Data Engineering & Platform Development: Design, develop, and maintain scalable data pipelines, data lakes, data warehouses, and AI-enabled data applications that support enterprise analytics, reporting, and Generative AI use cases. Data Ingestion & Processing: Build and optimize batch and real-time data pipelines using Python, Spark, Kafka, Airflow, and cloud-native services, ensuring reliable, high-performance data processing at scale. Generative AI & AI Solution Development: Develop and integrate Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, AI agents, prompt engineering, and enterprise knowledge repositories. Cloud & Infrastructure: Deploy and manage cloud-native data and AI solutions on AWS (S3, Redshift, Glue, EMR, Lambda, ECS, EKS, Bedrock, SageMaker), following DevOps and MLOps best practices for CI/CD, monitoring, governance, and scalability. Data Integration: Work closely with business stakeholders, data scientists, and application teams to integrate data pipelines, enterprise datasets, machine learning models, and GenAI services through APIs and cloud platforms. Security & Governance: Implement data governance, metadata management, data quality frameworks, authentication, authorization, and security controls aligned with enterprise standards and compliance requirements. Collaboration & Delivery: Partner with AI engineers, data scientists, analytics teams, and product managers to translate business requirements into scalable, production-ready data and AI solutions. Continuous Improvement: Adopt best practices in data engineering, AI development, coding standards, testing, observability, performance tuning, cost optimization, and emerging Generative AI technologies. Qualifications Qualifications Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, Engineering, or a related field. 6+ years of experience in Data Engineering, Big Data, Analytics, and/or AI application development. Strong proficiency in Python, SQL, Spark, and data processing frameworks, with experience building scalable data pipelines and data platforms. Hands-on experience with AWS Cloud services (S3, Redshift, Glue, EMR, Lambda, Bedrock, SageMaker), containerization (Docker, Kubernetes), and CI/CD pipelines. Experience with Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vector Databases, AI Agents, Prompt Engineering, and AI/ML model integration. Familiarity with modern data architectures, including Data Lakes, Data Warehouses, Streaming Platforms (Kafka), and cloud-native analytics ecosystems. Excellent problem-solving, communication, stakeholder management, and cross-functional collaboration skills. Additional Information 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]. Job Type (exemption status): Exempt position - Please see related compensation & benefits details below Business Function: Data Analytics Engineering Work Location: Bangalore Hallmark Office (IBS)--LOC_WDT_IBS

Responsibilities

Design and maintain scalable data pipelines, data lakes, and AI-enabled applications to support enterprise analytics and Generative AI use cases. Develop and integrate LLM-based solutions using RAG and vector databases while managing cloud-native infrastructure on AWS.