Senior Data Engineer, Defect Quality & Systems

Samsung•Austin, TX

13d•Onsite

About The Position

We are seeking a Senior Data Engineer to architect and optimize the foundation of our data ecosystem. In a 24/7 manufacturing environment generating terabytes of data, the reliability and scalability of our data pipelines are critical to factory success. In this role, you will not just move data; you will design the systems that ensure our engineers and data scientists have high-quality, high-performance data at their fingertips. You will bridge the gap between raw internal systems and actionable business intelligence, evolving our infrastructure from concept to high-impact reality while mentoring the next generation of data talent.

Requirements

BS or MS in Software Engineering, Computer Science, Data Science, Mathematics or related STEM/Engineering degree.
5+ years relevant experience.
Expert SQL Proficiency: Mastery of SQL for handling high-volume data, complex aggregations, and performance tuning within on-premise data stores.
Database Architecture: A proven track record of designing and modifying database schemas, with a deep understanding of normalization, data types, and relational integrity.
Data Visualization: Experience building interactive, user-centric dashboards (Tibco Spotfire, Tableau, or similar) that make complex data insights immediately visible.
Python Development: Ability to troubleshoot, optimize, and extend existing Python code to automate data workflows.
Analytical Problem Solving: A disciplined approach to root-cause analysis and a relentless attention to detail when debugging complex data discrepancies.
Communication Excellence: The ability to translate technical infrastructure challenges into business terms for stakeholders at all levels of the organization.

Nice To Haves

Semiconductor industry highly preferred but not required
Performance Optimization: ETL troubleshooting and database tuning, including a mastery of indexing and query plan analysis.
Big Data Ecosystems: Hands-on experience deploying and managing big-data technologies
Real-Time Streaming: Proficiency with event-streaming architectures and message brokers like Kafka or RabbitMQ.
Continuous Improvement Mindset: A passion for researching emerging data technologies and proactively optimizing existing logic to reduce latency and storage size.
Domain Knowledge: Familiarity with semiconductor process terminology and manufacturing workflows.

Responsibilities

Design, build, and monitor robust ETL/ELT pipelines that ingest massive data streams from diverse internal sources, including relational databases, APIs, and web services.
Implement advanced data cleaning, augmentation, and normalization workflows to ensure data integrity and prepare datasets for modeling and analysis.
Partner with internal customers to identify data gaps and integrate new sources, directly expanding the factory's decision-making capabilities.
Create and maintain high-performance dashboards and key metrics that serve as the "single source of truth" for business decisions across the factory.
Lead data initiatives from initial conceptualization through to deployment, ensuring the final data product delivers measurable business value.
Mentor junior team members in data engineering best practices, promoting a culture of clean code, scalable architecture, and rigorous documentation.