About this role
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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.
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Your responsibilities will include:
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Developing and maintaining scalable data pipelines and reusable datasets within a Databricks lakehouse environment
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Ingesting, validating, cleaning and transforming structured and unstructured data from multiple sources using Python, PySpark and SQL
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Building data models and reporting datasets that support Tableau and established analytics tools such as Spotfire
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Integrating established data warehouse and reporting systems with modern cloud analytics platforms
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Improving pipeline reliability, data quality and processing performance
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Implementing automated testing, monitoring, documentation and CI/CD practices
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Partnering with analysts, architects, developers and business stakeholders to deliver practical data solutions
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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