• You’ll build and maintain data pipelines and datasets that support reporting, visualization, machine learning and data-driven decision making across finance, sales, supply chain, marketing and other business functions. • Your responsibilities will include: • Developing and maintaining scalable data pipelines and reusable datasets within a Databricks lakehouse environment • Ingesting, validating, cleaning and transforming structured and unstructured data from multiple sources using Python, PySpark and SQL • Building data models and reporting datasets that support Tableau and established analytics tools such as Spotfire • Integrating established data warehouse and reporting systems with modern cloud analytics platforms • Improving pipeline reliability, data quality and processing performance • Implementing automated testing, monitoring, documentation and CI/CD practices • Partnering with analysts, architects, developers and business stakeholders to deliver practical data solutions • Providing technical guidance, reviewing code and mentoring other data engineer Requirements • 7+ years of experience in data engineering, including building and supporting production data pipelines • Strong SQL skills and a solid understanding of data modeling, database design and data warehousing • Hands-on experience with Databricks, Apache Spark and cloud data platforms • Strong proficiency in Python and PySpark • Experience developing ETL/ELT pipelines and integrating data from multiple source systems • Experience preparing reliable datasets for Tableau or comparable business intelligence tools • Familiarity with source control, automated testing and CI/CD practices • Ability to troubleshoot complex data issues and optimize pipeline performance • Strong communication skills and experience collaborating with technical teams and business stakeholders • Experience with Spotfire, Oracle, Informatica, R or data virtualization preferred • Databricks certification preferred