Sr. Data Engineer

Samsung Electronics•Los Angeles, CA

7d•$180,000 - $230,000

About The Position

Samsung TV Plus is a premium global entertainment service and is the most-used streaming app on Samsung Smart TVs. A leader in FAST, Samsung TV Plus offers hundreds of channels and thousands of shows and movies on-demand in the U.S. Globally, the streaming service carries over 3,500 ad-supported linear channels in 30 countries and is accessible on over 630M active devices. Samsung TV Plus is the exclusive home of Conan O’Brien TV, Letterman TV, and hundreds of additional exclusive channels available worldwide. Samsung TV Plus is available on Samsung TVs, Galaxy devices, Samsung Smart Monitors, and Family Hub. The Samsung TV Plus is seeking a Senior Data Engineer to join our Data Analytics & Insights team to architect, scale, and optimize our global data platform. You will own high-performance data infrastructure, design robust ETL/ELT pipelines, and manage our cloud data warehouse environment — directly enabling advanced analytics, ROI measurement, and AI deployment across global engineering and analytics teams.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related quantitative discipline (Master's preferred).
8+ years of professional experience in data engineering, backend software engineering, or data platform architecture.
Extensive hands-on experience designing and managing enterprise environments in Snowflake (or Databricks, BigQuery, or equivalent cloud data warehouses).
Advanced proficiency in Python and SQL (analytical functions, window functions, and query optimization).
Production experience with dbt (or equivalent SQL-based transformation frameworks).
Experience orchestrating complex pipelines using Apache Airflow (or Prefect, Dagster, or equivalent workflow orchestrators).
Practical experience with the AWS ecosystem (or GCP, or equivalent cloud platforms).
Familiarity with Infrastructure as Code (IaC) tools like Terraform (or CloudFormation, Pulumi, or equivalent tools) and CI/CD version control workflows.
Deep understanding of data warehousing methodologies and Star schema design.

Nice To Haves

Using tools like Snowflake DMFs, Great Expectations, Monte Carlo, or dbt test to ensure end-to-end pipeline reliability.
Functional understanding of BI server modeling layer integrations (e.g., PowerBI, Tableau, or equivalent).
Experience working with digital media, streaming analytics, or AdTech datasets.
Experience working with global teams across different time zones (specifically collaborating with Korea tech HQ).

Responsibilities

Own the technical design, implementation, and scaling of our enterprise cloud data warehouses and centralized cloud storage platforms. Lead performance tuning, cost optimization, and query scaling strategies.
Build, monitor, and maintain robust batch and streaming data pipelines using SQL, Python, and modern workflow orchestration engines to ingest high-volume, global streaming datasets.
Architect clean, modular, and optimized analytics schemas using automated data modeling and transformation frameworks to ensure reliable, analysis-ready datasets.
Establish rigorous data quality frameworks, observability metrics, and automated monitoring tests to ensure end-to-end pipeline reliability and prevent data downtime.
Partner with cross-functional engineering, analytics, and business stakeholders in LA and Korea HQ to translate complex business logic into scalable data schemas and robust systems.
Mentor junior engineers, establish best practices for data engineering (CI/CD, code reviews, version control), and champion modern data stack methodologies across the organization.