<p><strong>Overview</strong></p><p>We are seeking an experienced Data Engineer to join a growing data team supporting enterprise analytics, reporting, and data science initiatives. This role will focus on supporting and enhancing existing data pipelines while contributing to new development efforts within a modern data environment. The ideal candidate will have strong experience with Databricks, SQL, and Python, along with the ability to partner directly with business stakeholders and translate business requirements into scalable technical solutions.</p><p> </p><p><strong>POSITION: DATA ENGINEER</strong></p><p><strong>LOCATION: DALLAS, TX ONSITE</strong></p><p><strong>DURATION: 6-MONTH CONTRACT-TO-HIRE</strong></p><p> </p><p><strong>RESPONSIBILITIES</strong></p><ul><li>Develop, support, and enhance ETL and data pipeline solutions.</li><li>Design and build data transformations across Bronze, Silver, and Gold data layers within a Medallion Architecture environment.</li><li>Write, optimize, and troubleshoot complex SQL queries to support reporting, analytics, and operational business needs.</li><li>Develop and maintain data processing solutions using Python and PySpark within Databricks.</li><li>Partner directly with business stakeholders to gather requirements and translate business needs into technical solutions.</li><li>Monitor, troubleshoot, and resolve data pipeline issues while performing root cause analysis.</li><li>Design and maintain data warehouse and database models that support reporting, analytics, and data science initiatives.</li><li>Deliver trusted and certified datasets that power dashboards, self-service analytics, and business reporting.</li><li>Apply best practices related to data quality, testing, monitoring, performance optimization, documentation, and maintainability.</li><li>Collaborate with data engineers, analysts, data scientists, and business teams on strategic initiatives and ongoing support efforts.</li></ul>

<p><strong>REQUIREMENTS</strong></p><ul><li>2+ years of experience in Data Engineering, Data Warehousing, or a related field.</li><li>Strong hands-on experience with Databricks.</li><li>Advanced SQL skills including complex joins, window functions, CTEs, and query performance tuning.</li><li>Experience using Python for data processing and automation.</li><li>Experience with PySpark for large-scale data transformation and processing.</li><li>Experience developing and supporting ETL and data pipelines in production environments.</li><li>Hands-on experience working within a Medallion Architecture framework, including Bronze, Silver, and Gold data layers.</li><li>Experience with database and data warehouse modeling, including dimensional and normalized models.</li><li>Strong understanding of data quality, testing, monitoring, and production support best practices.</li><li>Ability to translate business requirements into effective technical solutions.</li><li>Strong communication skills and experience working directly with business stakeholders.</li><li>Strong troubleshooting, debugging, and root-cause analysis skills.</li><li>Experience working within Agile/Scrum development environments.</li></ul><p> </p><p><strong>PREFERRED QUALIFICATIONS</strong></p><ul><li>Experience working with inventory, merchandising, retail, wholesale distribution, supply chain, logistics, or replenishment data domains.</li><li>Experience with Spark, Delta Lake, and Unity Catalog.</li><li>Experience with cloud data platforms such as Snowflake, BigQuery, or Redshift.</li><li>Experience with orchestration tools including Airflow, Azure Data Factory, Prefect, or Dagster.</li><li>Familiarity with data quality frameworks and observability tools.</li><li>Experience with BI and analytics platforms such as Power BI or Sigma.</li><li>Experience supporting reporting, analytics, and data science initiatives.</li><li>Experience applying data engineering best practices including version control, code reviews, automated testing, monitoring, and performance optimization.</li><li>Strong documentation, organization, and collaboration skills.</li></ul>

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