Senior Engineer, Data Analytics Engineering

Company Description

At Western Digital, our vision is to power global innovation and push the boundaries of technology to make what you thought was once impossible, possible.

At our core, Western Digital is a company of problem solvers. People achieve extraordinary things given the right technology. For decades, we’ve been doing just that. Our technology helped people put a man on the moon.

We are a key partner to some of the largest and highest growth organizations in the world. From energizing the most competitive gaming platforms, to enabling systems to make cities safer and cars smarter and more connected, to powering the data centers behind many of the world’s biggest companies and public cloud, Western Digital is fueling a brighter, smarter future.

Binge-watch any shows, use social media or shop online lately? You’ll find Western Digital supporting the storage infrastructure behind many of these platforms. And, that flash memory card that captures and preserves your most precious moments? That’s us, too.

We offer an expansive portfolio of technologies, storage devices and platforms for business and consumers alike. Our data-centric solutions are comprised of the Western Digital®, G-Technology™, SanDisk® and WD® brands.

Today’s exceptional challenges require your unique skills. It’s You & Western Digital. Together, we’re the next BIG thing in data.

Job Description

• Integrating and maintaining the end-to-end data pipeline - to take data from source systems to target data repositories ensuring the quality and consistency of data is maintained at all times
• Monitor and tune data pipelines for optimal performance and efficiency.
• Support critical data processes running in production
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and provide technical solutions.
• Document data engineering processes, data flows, and architecture.

Qualifications

• Bachelor's in a relevant field (e.g., Data Science, Computer Science, Statistics, Engineering, Applied Sciences).
• 1+ years of experience in building data engineering pipelines and DevOps for ML applications.
• Proficient in programming languages like Pyspark/Python, SQL to engineer and transform data.
• Experience in designing and deploying data applications on cloud solutions, such as Azure or AWS, Edge, Dockers.
• Experience with CI/CD using Jenkins for applications.
• Experience with data modeling, ETL development, and data integration.
• Excellent communication and stakeholder management skills to understand requirements, act based on it.
• Demonstrated analytical and problem-solving skills particularly those that apply to a big data environment.

Additional Information

All your information will be kept confidential according to EEO guidelines.