Sr. Data Engineer

Position Summary

Role and Responsibilities

Key Responsibilities

Data Platform & Warehouse Architecture: 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.

Pipeline Development (ETL/ELT): 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.

Modern Data Modeling: Architect clean modular and optimized analytics schemas using automated data modeling and transformation frameworks to ensure reliable analysis-ready datasets.

Data Observability & Governance: Establish rigorous data quality frameworks observability metrics and automated monitoring tests to ensure end-to-end pipeline reliability and prevent data downtime.

Global Stakeholder Collaboration: 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.

Technical Leadership: Mentor junior engineers establish best practices for data engineering (CI/CD code reviews version control) and champion modern data stack methodologies across the organization.

Required Qualifications

Education: Bachelors degree in Computer Science Data Engineering Information Systems or a related quantitative discipline (Masters preferred).

Experience: 8 years of professional experience in data engineering backend software engineering or data platform architecture.

Core Technologies (or equivalent tools):

o Cloud Data Warehousing: Extensive hands-on experience designing and managing enterprise environments in Snowflake (or Databricks BigQuery or equivalent cloud data warehouses).

o Languages: Advanced proficiency in Python and SQL (analytical functions window functions and query optimization).

o Data Transformation: Production experience with dbt (or equivalent SQL-based transformation frameworks).

o Pipeline Orchestration: Experience orchestrating complex pipelines using Apache Airflow (or Prefect Dagster or equivalent workflow orchestrators).

o Cloud Infrastructure: Practical experience with the AWS ecosystem (or GCP or equivalent cloud platforms).

o 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.

Preferred Qualifications

Data Observability & Governance: Using tools like Snowflake DMFs Great Expectations Monte Carlo or dbt test to ensure end-to-end pipeline reliability.

BI Integration: Functional understanding of BI server modeling layer integrations (e.g. PowerBI Tableau or equivalent).

Media & AdTech Context: Experience working with digital media streaming analytics or AdTech datasets.

Cross-cultural Collaboration: Experience working with global teams across different time zones (specifically collaborating with Korea tech HQ).

Skills and Qualifications

Compensation for this role for a candidate based in Los Angeles California expected to be between $180000 and $220000. Actual pay will be determined considering factors such as relevant skills and experience and comparison to other employees in the role.

Regular full-time employees (salaried or hourly) have access to benefits including: Medical Dental Vision Life Insurance 401(k) Employee Purchase Program Tuition Assistance (after 6 months) Paid Time Off Student Loan Program (after 6 months) Wellness Incentives and many more.

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