Data Engineer

Join the Leader in Trading Cards!

MJ Holding Company, LLC is the largest distributor of sports trading cards and trading card games like Magic:
The Gathering and Pokémon— and we’re growing fast. Our success comes from passionate people who love what they do. At MJH, you’ll find a team that’s enthusiastic about the products we distribute, proud of the culture we’ve built, and committed to our success. If you’re driven and excited about the world of trading cards, we want you on our team!

The Data Engineer is a core technical leader within the data team, responsible for the design, architecture, and delivery of scalable, reliable data platforms that power the organization’s data warehouse, analytics, and business intelligence initiatives. This role goes beyond hands‑on development to include data architecture, solution design, technical direction, and mentorship. The Data Engineer partners closely with forecasting, application development, and business stakeholders to ensure the data ecosystem supports current and future business needs.

• Design and evolve the organization’s data architecture, including ingestion patterns, transformation layers, semantic models, and consumption frameworks.
• Lead architectural decisions for data warehousing and analytics platforms such as Snowflake, Databricks, Big Query, or similar technologies.
• Define and enforce standards for data modeling, naming conventions, schema design, and performance optimization.
• Evaluate and recommend tools, technologies, and architectural patterns that align with scalability, reliability, and cost efficiency goals.

• Design, build, and optimize robust ELT/ETL pipelines using tools such as dbt, Apache Airflow, and cloud‑native services (e.g., Azure Data Factory).
• Own end‑to‑end pipeline reliability, including orchestration, monitoring, alerting, and failure recovery.
• Develop and optimize complex SQL transformations, stored procedures, and performance‑critical queries.
• Implement scalable data processing solutions that support both batch and incremental/near‑real‑time use cases.

• Lead the design of enterprise data models, including dimensional (star/snowflake) and curated analytical models.
• Partner with analytics and business teams to translate requirements into semantic models, KPIs, and certified datasets.
• Ensure the data warehouse is optimized for self‑service BI, ad hoc analysis, and dashboard performance in tools such as Power BI or Tableau.
• Provide technical guidance on BI performance tuning, DAX/MDX best practices, and data usage patterns.

• Define and implement data quality frameworks, including validation, testing, and anomaly detection using tools such as dbt tests, Great Expectations, and custom Python solutions.
• Support data governance initiatives by helping establish data ownership, documentation, lineage, and access controls.
• Ensure data solutions adhere to security, privacy, and compliance requirements.

• Serve as a senior technical resource and mentor junior data engineers and analysts.
• Lead technical design discussions, architectural reviews, and documentation efforts.
• Collaborate cross‑functionally with business stakeholders, product teams, and engineering partners to deliver well‑designed data solutions.
• Influence data strategy and roadmap planning by providing architectural insight and trade‑off analysis.

• Candidate must be able to be on‑site in Bridgeview, IL to learn about the operation and business for ~6 months and can then transition to a hybrid office role.
• Ability to communicate complex technical concepts to both technical and non‑technical stakeholders.
• Proven analytical, problem‑solving, and system‑thinking mindset.
• Experience working in collaborative, version‑controlled environments using ITIL practices.
• Self‑directed, proactive, and comfortable owning ambiguous or complex problem spaces.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.

• Proven…