Job Description

Salary: $118,000 - 156,000 per year Requirements:

• We require 1-3 years of professional software or data engineering experience.
• We look for someone who learns quickly and can gather, assess, and interpret requirements effectively.
• We need a strong foundation in Python, plus deep SQL expertise and solid ETL/ELT knowledge for complex data transformations.
• We expect comfort reading and writing unit tests, and working within an established codebase and team conventions.
• We value familiarity with, or a strong desire to quickly learn, workflow orchestration tools such as Airflow or Managed Workflows for Apache Airflow.
• We need a basic understanding of pipeline concepts such as ingestion, idempotency, scheduling, and data quality.
• We prefer knowledge of several technologies such as Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL.
• We expect experience with Git-based version control and pull-request-driven code review workflows.
• We want strong communication skills, including asking clarifying questions, writing clear PR descriptions, and escalating blockers with useful context.
• We value a growth mindset, openness to feedback, and a commitment to better processes and reduced technical debt.
• Preferred, but not required: exposure to cloud data warehouses or lakehouses, data catalog and lineage tooling, reverse ETL patterns, PII masking, data security, RBAC/access governance, observability tools, or regulated industries.
• Preferred, but not required: familiarity with responsible handling of customer or PII-sensitive data.

• We will have you implement ingestion pipelines and Airflow DAGs from a senior engineers design, including code, unit tests, and documentation.
• We will have you support data security and governance efforts such as PII masking and access controls by following established patterns.
• We will have you contribute to data delivery work, including reverse ETL integrations, with guidance from senior engineers.
• We will have you extend existing pipelines by adding fields, incorporating review feedback, and applying learned patterns to future work.
• We will expect you to take on-call pages for pipeline failures, work through runbooks, and escalate with clear context when needed.
• We will have you pair with senior engineers on data integrity issues you cannot yet diagnose on your own.
• We will expect clear, reviewer-friendly PR descriptions and proactive clarifying questions before starting new work.
• We will want you to flag blockers early and explain them with context instead of going silent when stuck.
• We will have you build strong working relationships with BI analysts, other data engineers, and data scientists, helping to gather and refine requirements.
• We will have you participate in code and system inspections.
• We will have you help define and follow data engineering best practices.
• As you grow in the role, we will have you mentor more junior data engineers.

• Airflow
• AWS
• Cloud
• Databricks
• ETL
• Git
• Support
• MongoDB
• PostgreSQL
• Python
• RBAC
• SQL
• Security
• Snowflake
• Tableau
• dbt
• Datadog
• Kafka
• Network

More:

We are Fanatics, building a leading global digital sports platform that helps fans buy licensed merchandise, collect physical and digital trading cards and memorabilia, and bet through our growing Sportsbook and iGaming offering. Our platform serves a database of more than 100 million sports fans and supports around 900 sports properties, 2,500 athletes and celebrities, and over 2,000 retail locations worldwide. You will join our Data Engineering team, which owns the data foundation powering the business, working with Python ingestion pipelines, Airflow orchestration, and Snowflake/Databricks to move data reliably and securely from source to decision-ready output. This is an entry-level role with a clear growth path, close mentorship from senior and staff engineers, and a collaborative culture built on strong engineering practices, code review, clear standards, and ownership of outcomes. The role includes a salary range of $118,000-$156,000 USD and may involve in-person interview or onboarding components depending on location and role.

last updated 33 week of 2026

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