Engineer, Data Analytics Engineering at Western Digital

Biñan, Laguna, Philippines -

Full Time

Start Date

Immediate

Expiry Date

29 Sep, 26

Salary

0.0

Posted On

01 Jul, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Power BI, Data Visualization, Data Wrangling, Exploratory Data Analysis, Analytical Storytelling, R, Tableau, Matplotlib, Database Management, Machine Learning, Statistical Modeling, Process Analytics, Communication Skills, Collaboration

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 The Early Career Talent (ECT) -- Data Analytics / Computer Science will join Western Digital's Head Backend Business Unit under the BEST Program. This role sits within the Engineering organization and is designed to bridge the gap between manufacturing operations and data-driven decision-making. As the Head Backend BU operates in a high-precision, data-intensive manufacturing environment (slider processing and HGA assembly), the ability to collect, process, visualize, and interpret engineering data is increasingly critical to maintaining competitiveness and operational excellence. The ECT will support analytics initiatives, dashboard development, and process data interpretation alongside engineering and operations teams. The role is based in the Philippines (PHO) and reports to the Head Backend Engineering organization. Key responsibilities include: Supporting development of operational dashboards and data visualization tools for manufacturing KPIs (yield, throughput, defect rates) Assisting in data collection, cleaning, and analysis of process engineering data Building and maintaining reports using tools such as Python, SQL, Power BI, or equivalent Collaborating with engineers to translate data insights into actionable process improvements Participating in all BEST Program milestones including IDP reviews and Phase 2 applied analytics projects Contributing to automation of manual reporting processes across engineering functions This position is part of our Early Career program at WD. Our Early Career program is designed to support individuals beginning their professional career by providing foundational training through a structured onboarding, mentorship, and development curriculum. Qualifications REQUIRED: Bachelor's degree in Computer Science, Data Science, Information Technology, Statistics, or Engineering with a strong programming/analytics specialization Fresh graduate or maximum 1 year of work experience Demonstrated proficiency in at least one programming language (Python, R, SQL) Experience with data visualization (Power BI, Tableau, matplotlib, or similar) Strong quantitative and analytical academic background PREFERRED: Coursework or project work in machine learning, statistical modeling, or process analytics Exposure to manufacturing data, IoT sensor data, or time-series analysis Knowledge of database management (SQL Server, MySQL, or similar) Capstone, thesis, or competition experience in data analytics or AI/ML Basic understanding of engineering or manufacturing concepts SKILLS: Strong programming skills (Python and/or SQL minimum) Data wrangling, cleaning, and exploratory data analysis Dashboard and visualization development Analytical storytelling -- ability to translate data into business-relevant insights Collaborative and curious mindset, comfortable working in cross-functional engineering teams Good communication skills -- able to present findings clearly to non-technical stakeholders Strong written and verbal English communication Important Reminders: We provide free medical examination. We do not collect any original requirements. We do not collect any fees at any stage of the hiring process. 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: Biñan HICAP Office--LOC_HGST_PHL01

Responsibilities

Support the development of operational dashboards and data visualization tools to track manufacturing KPIs. Collaborate with engineering teams to clean process data and translate insights into actionable improvements.