Senior Data Engineer - Omni Channel

Overview

Here at Discount Tire, we celebrate the spirit of our people with extraordinary pride and enthusiasm. Our business has been growing for more than 60 years and now is the best time in our history to join us. We recognize that to remain the industry leader we must continue to grow and evolve our business in a rapidly changing industry. We are achieving this, not only by opening new stores, but by transforming our technological landscape and making data a central component of our strategy.

The Business Analytics team, one of the fastest growing teams in the company, is leading this change. We are responsible for driving the insights, recommendations, and developing the decision support tools that influence the strategic direction of the company.

• Lakehouse & Data Architecture
  • Design, develop, and maintain Databricks-based lakehouse solutions leveraging medallion architecture (Bronze, Silver, Gold) and Delta Lake.
  • Build scalable, high-performance analytical data models to support reporting, analytics, and downstream consumption.
  • Ensure data solutions align with enterprise standards for security, governance, scalability, and cost efficiency.
• Data Engineering & ELT Pipelines
  • Develop, test, and maintain batch and streaming ELT pipelines using Spark SQL.
  • Implement incremental data processing, dependency management, and idempotent pipeline patterns across multiple data sources.
  • Integrate structured and semi-structured data from transactional, digital, and third‑party systems into the lakehouse.
• Databricks Platform Development
  • Develop and maintain Databricks notebooks, workflows, and jobs across development, QA, and production environments.
  • Leverage Delta Lake features including ACID transactions, schema enforcement and evolution, and time travel.
  • Partner with platform and Dev Ops teams to support environment promotion, scheduling, and deployment automation.
• Data Quality & Reliability
  • Implement automated data quality checks, validation frameworks, and monitoring to ensure accuracy, completeness, and timeliness of data.
  • Proactively identify and resolve data issues, ensuring reliable data availability for business partners.
• Performance Optimization & Tuning
  • Troubleshoot data pipeline and query performance issues and implement optimizations related to Spark execution, partitioning, file sizing, and data layout.
  • Document root‑cause analysis and corrective actions and provide recommendations to improve system performance and reliability.
• Production Ownership & Operations
  • Own data pipelines end-to-end in production, including monitoring, alerting, incident response, and operational support.
  • Contribute to runbooks, operational documentation, and continuous improvement of production readiness practices.
• Programming & Standards
  • Write clean, maintainable, and well‑tested code using Python (PySpark) and SQL.
  • Contribute to data engineering standards, reusable frameworks, and best practices across the Analytics Engineering team.
• Documentation & Reviews
  • Produce clear technical documentation, including design specifications and data flow diagrams.
  • Participate in design reviews and code reviews, providing constructive feedback to ensure quality and consistency.
• Collaboration & Stakeholder Engagement
  • Collaborate closely with data engineers, analytics engineers, data scientists, digital analysts, and business stakeholders to translate business needs into scalable data solutions.
  • Work cross‑functionally with project managers, platform teams, and external partners to deliver high‑impact analytics capabilities.
• Mentorship & Technical Leadership
  • Mentor and support less experienced data engineers through technical guidance and best‑practice sharing.
  • Lead technical design discussions for complex datasets and influence architectural decisions within the team.
• Continuous Improvement
  • Stay current with emerging data engineering technologies, trends, and industry best practices.
  • Identify opportunities to improve efficiency, reliability, and scalability across data engineering workflows.
• Perform other duties as assigned.

• 5+ years of experience in data engineering, data integration, or analytics engineering…