Data Engineer

Location: Sunnyvale, TX, United States

Department: Manufacturing & Operations

Design, build, and maintain scalable data pipelines using orchestration frameworks such as Airflow and Dagster to support reliable data ingestion and transformation across multiple upstream systems 35%; Develop and manage a centralized data platform that integrates diverse data sources (e.g., APIs, databases, third-party systems), ensuring data quality, consistency, and availability for downstream consumption 20%; Implement robust data modeling and transformation processes (ETL/ELT) to structure raw data into curated datasets optimized for analytics and business use cases 15%; Enable self-service data access by building data services, semantic layers, and AI-powered tools (e.g., agents, query interfaces) that allow business users to easily explore and consume data 10%; Collaborate with cross functional teams (data scientists, analysts, and business stakeholders) to define data requirements and ensure scalable, production-grade data solutions 10%; Design and maintain monitoring, logging, and alerting systems to ensure pipeline reliability, performance, and data integrity 5%; Apply software engineering best practices (CI/CD, version control, testing) to develop and deploy data infrastructure and pipeline code in a cloud-based environment 5%. Up to 5% domestic travel may be required for internal meetings. Partial telecommuting permitted; on-site at 11601 Wilshire Blvd., Los Angeles, CA 90025 when not telecommuting. Salary: $162,300 - $182,300 per year.

MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Computer Science, Computer Engineering, Engineering Management, or a related field, plus 4 years of professional experience as a Data Scientist, Data Analyst, or any occupation, job title, or position performing data-driven software engineering and analytics development.

Must also have experience in the following: 4 years of professional experience collaborating with cross functional stakeholders (including business, product, engineering, and data teams) to translate business requirements into scalable analytical solutions; 4 years of professional experience applying software engineering best practices to analytical codebases, including version control (Git), peer code reviews, and modular code development; 3 years of professional experience writing complex SQL queries and performing data mining across large relational or cloud-based data warehouse environments; 3 years of professional experience designing and developing data pipelines using Python (including Pandas and PySpark) and ETL processes to transform and prepare large datasets for analytical use; 3 years of professional experience developing and optimizing data models, custom datasets, and data structures to support evolving analytical and reporting needs; 3 years of professional experience designing and developing business intelligence dashboards and automated reporting solutions SQL and visualization tools (including Tableau, QuickSight, or Looker) to support KPI tracking and executive reporting; 3 years of professional experience maintaining and optimizing cloud-based data solutions within AWS environments to ensure performance, reliability, and scalability; 3 years of professional experience conducting statistical analyses, including hypothesis testing, regression analysis, and product experimentation to inform business decision-making.

CONTACT: Apply online at fanaticsinc.com/careers or email resume to: WorkWithFanatics@FanaticsInc.com. Must specify Ad Code AMKM in subject line. #LI-DNI #LI-DNP