Hybrid Data Engineer — Pipelines, ETL & Analytics

Fanatics Collectibles; Sunnyvale (TX); On-site; USD 162,000 - 182,000; Full time

Benefits offered by this job

Partial telecommuting

On-site LA office

Job summary

Fanatics Collectibles is seeking a Data Scientist to design and maintain scalable data pipelines and a centralized analytics platform. You will integrate diverse data sources, build ETL/ELT processes, and empower self-service analytics for business stakeholders in a cloud environment.

The role requires collaboration with data scientists and analysts, strong SQL and Python skills, and experience with AWS and BI dashboard tools.

Qualifications

• 4+ years of experience building analytical solutions with cross-functional stakeholders.
• 4 years collaborating with business, product, engineering, and data teams.
• 3 years writing complex SQL and data mining in cloud data warehouses.
• 3 years building data pipelines with Python ETL/ELT.
• 3 years developing data models and datasets for analytics.
• 3 years designing BI dashboards and automated reports.

Responsibilities

• Design, build, and maintain scalable data pipelines using Airflow and Dagster.
• Develop a centralized data platform integrating diverse data sources for analytics.
• Implement robust ETL/ELT processes to structure data for reporting.
• Enable self-service data access via semantic layers and data services.
• Collaborate with data scientists, analysts, and business stakeholders on data needs.
• Design and maintain monitoring, logging, and alerting for pipelines.
• Apply software engineering best practices (CI/CD, Git, testing) in cloud environments.
• Up to 5% domestic travel for internal meetings; telecommuting available; on-site LA office.

Skills

Python

SQL

ETL/ELT

Airflow

Dagster

Data Modeling

BI Dashboards

AWS

Git

Pandas PySpark

Education

Bachelor's degree in CS/Engineering/Related field

Tools

Tableau

Looker

QuickSight

Job description

Fanatics Collectibles is seeking a Data Scientist to design and maintain scalable data pipelines and a centralized analytics platform. You will integrate diverse data sources, build ETL/ELT processes, and empower self-service analytics for business stakeholders in a cloud environment.

The role requires collaboration with data scientists and analysts, strong SQL and Python skills, and experience with AWS and BI dashboard tools.