About Arena Club If you’re fascinated by sports cards and memorabilia, your search ends here. Arena Club is pioneering the collectibles domain by introducing the first-ever digital card show. Spearheaded by 5x World Series Champion Derek Jeter and serial entrepreneur Brian Lee, Arena Club has developed a fully digital marketplace.

This innovative platform is built on trust, transparency, and fun, featuring grading authentication, vaulting, and digital pack openings for collectors to build and showcase their collections in a personalized online showroom from anywhere in the world.

About The Role

We are seeking a Senior Data Engineer to help strengthen Arena Club’s strategic decision-making, enhance operational performance, and integrate data across the company to unlock deeper insights into customer behavior and market performance. As a key individual contributor, you’ll focus on building and maintaining reliable data pipelines, improving data quality, and ensuring data is well-instrumented, accessible, and structured to support meaningful analysis. You will work with existing tools and systems, including Mixpanel and AWS-based data infrastructure, partnering closely with engineering and business teams across product, operations, and the marketplace.

This is a hands-on role for someone who enjoys owning execution, operating in evolving data environments, and incrementally improving how data is collected, processed, and used to drive better business decisions.

What You Will Do

Current State — Production Data Warehouse • Maintain and optimize inbound and outbound ETL pipelines built on AWS Glue (Python Shell Spark ETL) • Manage Redshift cluster performance across various schemas • Own integrations with SaaS data sources via AppFlow and direct connectors • Operate outbound distribution pipelines to external vendors • Manage infrastructure, alerting, and migration state tracking Future State — Medallion Architecture Real-Time • Lead the migration from ad-hoc SQL scripts to a Bronze/Silver/Gold medallion architecture with dbt as the transformation layer • Design and implement dimensional models, i.e., fact tables and dimensions • Build the Silver staging layer • Architect the real-time CDC pipeline • Implement data contracts and governance at the Silver layer to insulate downstream consumers from source changes Data Archival Cost Optimization • Implement a hot/cold storage strategy via Redshift Spectrum • Build the Unified Access Layer • Design and automate Glue jobs • Configure S3 lifecycle policies for progressive cost reduction

Qualifications

• 5+ years in data engineering with production pipeline ownership (not just analytics or BI) • Deep AWS experience: Glue (both Python Shell and Spark ETL), Redshift, S3, IAM, EventBridge, Lambda, AppFlow • Strong SQL: complex joins, window functions, MERGE/UPSERT patterns, Redshift-specific optimization (sort keys, dist keys, VACUUM/ANALYZE) • Python fluency: boto3, data processing libraries, writing production Glue scripts (not just notebooks) • Dimensional modeling: star schemas, fact/dimension design, SCD Type 1 and Type 2 implementation • dbt: hands-on experience building and maintaining staging, intermediate, and mart models with tests and documentation • Data warehouse operations: schema migration, incremental loads, backfill strategies, monitoring, and alerting • Hands-on experience using AI tools (Claude or Cursor preferred; other agentic tools welcome) to ship code, build agents, and automate workflows

Preferred Qualifications

• Redshift Spectrum: experience with external schemas, Parquet/Hive partitioning, and unified hot/cold querying • CDC / streaming: Postgres WAL, Debezium, EventBridge, or similar change data capture pipelines • Data Mesh concepts: domain-oriented ownership, data-as-a-product thinking, federated governance • AppFlow SaaS integrations: configuring and troubleshooting managed connectors for Stripe, Zendesk, Mixpanel, etc.