Data Engineer
Onsite - Dallas, TX
Must be able to do an onsite interview and work onsite 5 days per week
As a Data Engineer, you’ll partner closely with our Principal Data Engineers to keep data pipelines healthy, resolve bugs, and deliver well-modeled, trusted data for reporting and analytics. You’ll spend most of your time writing SQL and Python, designing and optimizing database models, and helping deliver trusted certified data that power dashboards, self-service analytics, and data science.
The ideal candidate will have experience working with Databricks and medallion architecture, including Bronze, Silver, and Gold data layers. Experience applying data engineering best practices for data quality, performance, testing, monitoring, documentation, and maintainability is important.
Experience with retail or wholesale distribution data—such as sales, inventory, merchandising, logistics, and supply chain—is strongly preferred.
Top Skills Details
- Databricks
- SQL
- Python
- Medallion architecture (Bronze, Silver, and Gold)
Work Environment
This position will be onsite at the new Dallas-area IT delivery center in Coppell, TX, or at the corporate headquarters in Fort Wayne, IN.
Additional Skills & Qualifications
- Operational mindset with strong debugging and root-cause analysis skills.
- Clear and concise communicator who can translate business needs into technical tasks.
- Collaborative, service-oriented teammate who is comfortable partnering with Principal Data Engineers and supporting analysts.
- Organized and detail-oriented, with strong documentation habits.
- Familiarity with Agile/Scrum and the software development lifecycle.
- Experience applying data engineering best practices, including version control, code reviews, automated testing, monitoring, and performance optimization.
Required
- Strong SQL skills, including advanced joins, window functions, CTEs, and performance tuning.
- Python experience for data processing and automation using pandas or PySpark.
- Hands-on database and data warehouse modeling experience, including dimensional and normalized modeling.
- Experience developing and supporting data pipelines using a medallion architecture with Bronze, Silver, and Gold layers.
- Understanding of data quality, testing, monitoring, and production support best practices.
- Experience working with retail data domains such as sales, inventory, products, pricing, merchandising, replenishment, logistics, or supply chain is preferred.
Preferred/Plus
- Databricks, including Spark, Delta Lake, and Unity Catalog.
- Cloud data platforms such as Databricks, Snowflake, BigQuery, or Redshift.
- Job orchestration tools such as Airflow, Azure Data Factory, Prefect, or Dagster.
- Data quality frameworks and observability tools.
- Familiarity with BI ecosystems such as Power BI or Sigma.
Business Challenge
The Do it Best data team has a significant portfolio of project work planned for the start of the fiscal year. The organization is expanding its data engineering capacity to support these priorities and increase its long-term full-time capabilities.