Sr. Data Engineer

Samsung•Los Angeles, CA

About The Position

Samsung TV Plus is a premium global entertainment service committed to delivering exceptional experiences for everyone and every moment. As a leader in FAST with more than 100 million monthly active users, Samsung TV Plus offers thousands of shows and movies on-demand all in one place. The streaming service carries over 4,300 ad-supported linear channels across 30 countries and is accessible exclusively on active Samsung devices. Samsung TV Plus is the exclusive FAST home to curated channels and live events including the 2025 Jonas Brothers’ JONAS 20 Tour, Letterman TV, Conan O’Brien TV, The Ringer from Spotify, BillboardTV, and top digital Creators featuring Mark Rober TV, Dhar Mann TV and Michelle Khare’s Challenge Accepted. Samsung TV Plus is available on Samsung TVs, Galaxy devices, Samsung Smart Monitor, 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.
Cloud Data Warehousing: Extensive hands-on experience designing and managing enterprise environments in Snowflake (or Databricks, BigQuery, or equivalent cloud data warehouses).
Languages: Advanced proficiency in Python and SQL (analytical functions, window functions, and query optimization).
Data Transformation: Production experience with dbt (or equivalent SQL-based transformation frameworks).
Pipeline Orchestration: Experience orchestrating complex pipelines using Apache Airflow (or Prefect, Dagster, or equivalent workflow orchestrators).
Cloud Infrastructure: Practical experience with the AWS ecosystem (or GCP, or equivalent cloud platforms).
Infrastructure & CI/CD: Familiarity with Infrastructure as Code (IaC) tools like Terraform (or CloudFormation, Pulumi, or equivalent tools) and CI/CD version control workflows.
Data Modeling: 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.