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# Sr. Data Engineer

- **Company:** Samsung
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $210,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Query Performance, Java (Programming Language), Airflow, Amazon Web Services, Big Data, Code Coverage, Computer Programming, Continuous Integration, Information Engineering, Data Governance, Data Systems, Data Warehousing, Python (Programming Language), Machine Learning, Standard Sql, Software Construction, Data Streaming, Workflow Management Systems, Data Processing, Snowflake, Apache Spark, Containerization, Kubernetes, Information Technology, Apache Flink, Data Analytics, Apache Kafka, Data Pipelines, Docker, Golang
- **Published:** July 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c5023af7cec558f8

## About the Role

* Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related field; or equivalent practical experience
 * Programming experience in Python; GoLang and Java preferred; Scala nice to have
 * Understanding of data technologies including Snowflake, Spark, and SQL
 * Experience with or eagerness to learn streaming data systems such as Kafka, Flink, or Kinesis
 * Familiarity with workflow orchestration tools (e.g., Airflow) or willingness to learn
 * Understanding of data modeling and software engineering best practices
 * Strong communication and collaboration skills with growth mindset

Experience Levels:

 * Entry Level (0-2 years): New graduates or early-career professionals with relevant coursework, internships, or personal projects
 * Mid Level (2-5 years): Solid experience with data systems and data engineering
 * Senior Level (5+ years): Proven track record of building and operating large-scale data systems with technical leadership experience

Preferred Qualifications:

 * Experience with cloud platforms, particularly Amazon Web Services (AWS)
 * Background in digital advertising, programmatic systems, or ad measurement platforms
 * Experience with containerization and orchestration (Kubernetes, Docker)
 * Experience with data quality frameworks and automated validation pipelines
 * Knowledge of statistical methods and data-driven performance analysis
 * Experience with infrastructure-as-code and CI/CD automation
 * Experience with large-scale reporting, data warehousing, or billing systems

## Description

Sr Data Engineer - Samsung Ads, We are seeking Data Engineers at all experience levels to join the Performance & Reach engineering organization within Samsung Ads. You will contribute to the foundational data systems that power our Performance Ads and Reach Demand product lines, working with large-scale advertising datasets to support campaign delivery, reporting, and billing for global advertisers.
You'll work closely with Product, Data Science, Machine Learning, and Application Engineering teams to deliver production-grade data solutions. This position offers significant growth opportunities and mentoring, with the potential to advance into technical leadership roles., * Contribute to scalable, high-performance data pipelines for ingestion, transformation, and analytics across large-scale advertising datasets

 * Support development and optimization of data models for reporting, billing, and campaign delivery systems
 * Participate in building and maintaining batch and real-time data processing workflows handling billions of events daily
 * Help ensure data quality, completeness, and accuracy through automated validation frameworks and reconciliation checks
 * Contribute to Snowflake optimization including query performance and cost-efficient data processing patterns
 * Support workflow orchestration for multi-stage data pipelines
 * Follow engineering standards for CI/CD pipelines, test coverage, and deployment quality gates

Technical Growth & Leadership:

 * Collaborate with cross-functional and cross-site teams to translate business requirements into technical solutions
 * Participate in architecture and design reviews for data systems
 * Learn and apply data engineering best practices and operational excellence
 * Develop prototypes and contribute to proofs of concept
 * Adopt AI-assisted development practices and GenAI tool adoption


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