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Data Engineer II

Ciudad de México, Mexico

Live, first seen by us 36 days ago
Pay
Pay not listed
Work setting
On-site — work setting source
Work setup in the employer’s posting: Collectibles Onsite 5 Days
From the employer’s posting
Employment
Not stated

What you’ll work on

Full posting
  • Develop, deploy, and maintain cloud-native data pipelines across structured and unstructured sources

  • Build and optimize data models in relational and NoSQL databases

  • Implement data quality, observability, and reliability checks

  • Support Snowflake data modeling for Topps datasets via Shopify APIs

  • Support and enhance a Terraform project for Snowflake RBAC

From the employer’s posting
Develop, deploy, and maintain components of cloud-native data pipelines, integrating a variety of structured and unstructured data sources
Build and optimize data models in relational and NoSQL databases to support scalable data access patterns
Implement and monitor data quality, observability, and reliability checks using modern best practices
Support and enhance Snowflake data modeling for Topps-related datasets and analytics pipelines via Shopify APIs
Support and enhance Terraform project for Snowflake RBAC

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience
  • 2+ years of experience in data engineering or software engineering roles with a focus on backend data systems
  • Proficiency in **Python** , **SQL** , and **dbt** for data manipulation and pipeline development
  • Familiarity with **Shopify** APIs
  • Experience with Snowflake including performance tuning, schema design, and query optimization
  • Experience with cloud platforms (AWS preferred), and tools like Lambda, S3, Glue, or similar
Qualification wording
Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience
2+ years of experience in data engineering or software engineering roles with a focus on backend data systems
Proficiency in **Python** , **SQL** , and **dbt** for data manipulation and pipeline development
Familiarity with **Shopify** APIs
Experience with Snowflake including performance tuning, schema design, and query optimization
Experience with cloud platforms (AWS preferred), and tools like Lambda, S3, Glue, or similar
Education & alternatives
Basic Qualifications - Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience - 2+ years of experience in data engineering or software engineering roles with a focus on backend data systems

About Fanatics Collectibles

Fanatics is building a leading global digital sports platform.

In the employer’s words · Read in context

Apply at Fanatics Collectibles

Posting record

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Status in our records
Live
First seen by us
Sep 29, 202636 days ago
Recorded sightings
76
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 36

Similar jobs usually come down between day 6 and day 54.

From 10,782 similar postings that came down. Coming down is not always a hire.

Fanatics Collectibles is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • dbt
  • NoSQL
  • S3
  • Snowflake
  • Spark
  • Terraform
  • Airflow
Where the posting names them
- 2+ years of experience in data engineering or software engineering roles with a focus on backend data systems - Proficiency in **Python** , **SQL** , and **dbt** for data manipulation and pipeline development - Familiarity with **Shopify** APIs
- Familiarity with distributed data processing tools (e.g., Spark, Airflow) and modern orchestration - Working knowledge of both SQL and NoSQL databases and data modeling techniques - Comfortable working in a fast-paced environment with iterative product development
- Experience with Snowflake including performance tuning, schema design, and query optimization - Experience with cloud platforms (AWS preferred), and tools like Lambda, S3, Glue, or similar - Familiarity with distributed data processing tools (e.g., Spark, Airflow) and modern orchestration
- Develop, deploy, and maintain components of cloud-native data pipelines, integrating a variety of structured and unstructured data sources - Build and optimize data models in relational and NoSQL databases to support scalable data access patterns - Implement and monitor data quality, observability, and reliability checks using modern best practices
The Role As a Data Engineer II, you will help scale and evolve our data infrastructure as we build greenfield systems and develop a modern, cloud-native data stack. This FTE role will be primarily dedicated to supporting the Topps data engineering platform. You will also contribute to Snowflake architecture, modeling, and optimization, ensuring strong foundations for analytics, business intelligence, and operational data products. - Develop, deploy, and maintain components of cloud-native data pipelines, integrating a variety of structured and unstructured data sources
- Implement and monitor data quality, observability, and reliability checks using modern best practices - Support and enhance Snowflake data modeling for Topps-related datasets and analytics pipelines via Shopify APIs - Support and enhance Terraform project for Snowflake RBAC
- Support and enhance Snowflake data modeling for Topps-related datasets and analytics pipelines via Shopify APIs - Support and enhance Terraform project for Snowflake RBAC - Collaborate closely with data engineers, analysts, product managers, and business stakeholders to understand data needs and deliver usable solutions
- Familiarity with **Shopify** APIs - Experience with Snowflake including performance tuning, schema design, and query optimization - Experience with cloud platforms (AWS preferred), and tools like Lambda, S3, Glue, or similar
- Experience with cloud platforms (AWS preferred), and tools like Lambda, S3, Glue, or similar - Familiarity with distributed data processing tools (e.g., Spark, Airflow) and modern orchestration - Working knowledge of both SQL and NoSQL databases and data modeling techniques

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

About Us

Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. 

 

About Fanatics Collectibles

Fanatics Collectibles is the home of sports cards, trading cards, and collectibles for over 100 million fans worldwide. As part of the global Fanatics platform, we're rebuilding how collectors discover, buy, sell, and experience their hobby with world class technology and product experiences.

As part of Fanatics Collectibles’ continued global growth, we are establishing a new technology hub in Mexico City focused on operational excellence, platform scalability, trust, and customer experience. This team partners closely with Customer Experience (CX), Trust & Safety, Fraud Prevention, Payments, and Financial Operations organizations to build scalable systems and operational tooling that support millions of users and transactions globally.

The Role

As a Data Engineer II, you will help scale and evolve our data infrastructure as we build greenfield systems and develop a modern, cloud-native data stack. This FTE role will be primarily dedicated to supporting the Topps data engineering platform. You will also contribute to Snowflake architecture, modeling, and optimization, ensuring strong foundations for analytics, business intelligence, and operational data products.

  • Develop, deploy, and maintain components of cloud-native data pipelines, integrating a variety of structured and unstructured data sources
  • Build and optimize data models in relational and NoSQL databases to support scalable data access patterns
  • Implement and monitor data quality, observability, and reliability checks using modern best practices
  • Support and enhance Snowflake data modeling for Topps-related datasets and analytics pipelines via Shopify APIs
  • Support and enhance Terraform project for Snowflake RBAC
  • Collaborate closely with data engineers, analysts, product managers, and business stakeholders to understand data needs and deliver usable solutions
  • Participate in code reviews (Gand adopt engineering standards aligned to a high-performing data engineering culture
  • Contribute to onboarding and documentation of data sources, transformations, and pipelines
  • Continuously learn and adapt new technologies to improve system performance and maintainability

Basic Qualifications

  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent practical experience
  • 2+ years of experience in data engineering or software engineering roles with a focus on backend data systems
  • Proficiency in **Python** , **SQL** , and **dbt** for data manipulation and pipeline development
  • Familiarity with **Shopify** APIs
  • Experience with Snowflake including performance tuning, schema design, and query optimization
  • Experience with cloud platforms (AWS preferred), and tools like Lambda, S3, Glue, or similar
  • Familiarity with distributed data processing tools (e.g., Spark, Airflow) and modern orchestration
  • Working knowledge of both SQL and NoSQL databases and data modeling techniques
  • Comfortable working in a fast-paced environment with iterative product development

Code-Writing Contribution

This is a hands-on engineering role. A successful TP2 Data Engineer will be expected to regularly write clean, maintainable code to support ingestion pipelines, transformation logic, and data validation. Contributions are typically reviewed by senior engineers and integrated into production workflows.

 

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Ciudad de México, Mexico

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