Data Engineer II - (Remote)
About Our Client
The organization operates a global digital sports platform that connects sports fans with licensed merchandise, collectibles, and gaming opportunities. It serves a vast network including sports leagues, teams, athletes, and retail partners, offering products and services that span commerce, collectibles, and betting. The platform supports over 100 million sports fans worldwide and maintains a significant presence through numerous retail locations and partnerships.
About the Opportunity
The Data Engineer II is responsible for implementing and supporting data ingestion pipelines within the data engineering team, contributing to the reliable delivery and governance of data that powers business decisions. This role focuses on executing well-defined tasks under guidance, ensuring data quality and security, and collaborating with stakeholders to support data-driven operations.
Responsibilities
- Implement ingestion pipelines and Airflow DAGs based on senior engineers' designs, including coding, testing, and documentation
- Support data security and governance efforts such as PII masking and access controls
- Assist with data delivery work, including reverse ETL integrations
- Extend existing data pipelines and incorporate feedback
- Respond to pipeline failures and follow runbooks, escalating issues with context
- Collaborate with senior engineers on complex data integrity issues
- Write clear pull request descriptions and ask clarifying questions before starting work
- Communicate blockers early and effectively
- Build strong relationships with internal stakeholders to clarify requirements
- Participate in code and system inspections
- Help define and follow data engineering best practices
- Mentor junior data engineers as experience grows
Requirements
- 1 to 3 years of professional software or data engineering experience
- Proficiency in Python and deep understanding of SQL with complex ETL/ELT transformations
- Ability to write unit tests and work within established codebases
- Familiarity or willingness to learn Airflow or similar orchestration tools
- Understanding of data pipeline concepts including ingestion, idempotency, scheduling, and data quality
- Knowledge of technologies such as Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, or PostgreSQL
- Experience with Git-based version control and PR-based code reviews
- Strong communication skills including asking questions and escalating issues with context
- Growth mindset with openness to feedback and process improvement