Software Engineering, Data Infrastructure

NVIDIA•Us, CA

About The Position

The NVIDIA Operations organization is seeking a software engineering professional for the position of System Data, Software Engineer. As a member of our team you will be an integral part of building ETL pipelines, custom data pipelines and data analysis. You will support initiatives for the Data Platform, Reporting, and Analytics. Your work will turn data into information leading to insights and business results.

Requirements

Bachelor’s or Master’s degree in Computer Science, or equivalent experience with programming knowledge (e.g., Python, Database architectures, Cloud Services etc.)
2+ years of relevant experience
Experience in defining and building projects, collecting requirements, setting timelines, and delivering results.
Experience maintaining data warehouses/data lakes for complex data ecosystems.
Working knowledge of Amazon Web Services, Airflow, Docker, Spark, Scala.
Strong Python experience with a focus on data extraction and transformations.
Experience with structured data formats such as Parquet and Protobuf.

Nice To Haves

Demonstrated expertise in software engineering with a strong emphasis on data engineering.
Experience in setting up AWS infrastructure from scratch and automating deployment processes.
Proven experience crafting and optimizing ETL pipelines using tools like Spark, SQL, and cloud services, where standard work flows fail because of data sizes.
An understanding of operational processes in semiconductor chips, boards, systems, and servers.
Self-starter with a positive problem-solving outlook, ability to multitask, and strong organizational skills.
Passion for solving complex software problem that span across multiple domains.

Responsibilities

Designing, planning, and implementing custom cloud designs with team members to meet our growing data needs.
Work with data from testing semiconductor chips, boards, systems, and servers.
Develop a set of custom in-house tools to service the hardware and product teams.
Transforming data into reporting, analytics, and custom visualizations for large scale data analysis.
Maintain and expand custom ETL Pipelines in Athena.
Design and implement framework modules to extract data from various systems, validate integrity, apply business transformations, and store data in a Data Lake (AWS).
Build, scale, and optimize streaming pipelines for data storage and analytics on complex data sources.
Take ownership of data transformation and reporting to support hardware engineering teams.