Data Engineer II

Fanatics Betting & Gaming

. Implement ingestion pipelines and Airflow DAGs from senior engineers' designs, including code, unit tests, and documentation .

Posted 11/9/2026full-timeRemote • New York • United StatesJunior💰 $118,750 - $156,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Python and SQL for data engineering, with a strong focus on ETL/ELT processes and data quality. Capable of implementing and maintaining ingestion pipelines using Airflow while ensuring data security and governance.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyETL/ELT ProcessesAirflow ImplementationData Governance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringUnit TestingCode ReviewData TransformationIngestion PipelinesIdempotencySchedulingData QualityRequirements AnalysisMentoring

Soft Skills

Strong CommunicationCollaborationGrowth MindsetProblem-SolvingRelationship Building

Tools & Technologies

AirflowSnowflakeDatabricksAWSDbtTableauMongoDBPostgreSQLGitVersion Control

Industry Keywords

Data SecurityGovernancePII MaskingData IntegrityBI AnalystsData ScientistsData Engineers

Tech Stack

Tools & technologies

AirflowApacheAWSETLMongoDBPostgresPythonSnowflakeSQLTableau

About the role

Key responsibilities & impact

Implement ingestion pipelines and Airflow DAGs from senior engineers' designs, including code, unit tests, and documentation
Support data security and governance work, including PII masking and access controls
Contribute to reverse ETL and other data delivery work under senior engineer guidance
Extend existing pipelines and apply review feedback
Take on-call pages for pipeline failures, follow runbooks, and escalate with clear context
Pair with senior engineers on data integrity issues
Write reviewer-friendly pull request descriptions and ask clarifying questions
Flag blockers early
Build relationships with BI analysts, data engineers, data scientists, and other internal stakeholders
Gather and clarify requirements
Conduct and participate in code and system inspections
Help define and follow data engineering best practices
Mentor more junior data engineers as the role develops

Requirements

What you’ll need

1–3 years of professional software or data engineering experience
Strong ability to gather, evaluate, and analyze requirements
Solid foundation in Python
Deep understanding of SQL and ETL/ELT for complex data transformations
Ability to read and write unit tests and work within an established codebase and conventions
Familiarity with or eagerness to quickly learn Airflow / Managed Workflows for Apache Airflow
Basic understanding of ingestion, idempotency, scheduling, and data quality
Knowledge of several of Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL
Familiarity with Git-based version control and pull-request code review workflows
Strong communication skills, including asking clarifying questions, writing clear PR descriptions, and escalating blockers with useful context
Growth mindset and ability to apply review feedback and champion best practices

Benefits

Comp & perks

Base salary and bonus
Benefits information provided at https://benefitsatfanatics.com/
Potential in-person onboarding experience through Launching into Better: LIVE for full-time, non-seasonal hires
Company-paid or supported travel/participation for applicable onsite interviews or onboarding sessions (requirements confirmed by role and location)