The Role
Builds and maintains scalable data pipelines and reusable datasets in Databricks. Ingests, validates, transforms, and models structured and unstructured data using Python, PySpark, and SQL. Integrates warehouse and cloud analytics systems, supports Tableau and Spotfire reporting, improves reliability and performance, and implements testing, monitoring, documentation, and CI/CD. Collaborates with technical and business stakeholders while providing technical guidance, code reviews, and mentorship.
Summary Generated by Built In
- 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
Skills Required
- 7+ years of experience in data engineering, including production data pipelines
- Strong SQL skills and 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 or ELT pipelines and integrating 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 and collaboration skills with technical teams and business stakeholders
- Experience with Spotfire, Oracle, Informatica, R, or data virtualization
- Databricks certification
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The Company
What We Do
Bitful is a new kind of technology consulting firm: One that puts humans first. Together, we build future-proof, open, explorable data systems and perform cloud-computing marvels. We profoundly solve app challenges, and engineer game-changing digital products. And we do all of the above to create and fund opportunities for underserved communities who deserve to be every bit as supported, connected, and inspired as we are at Bitful. Better tech for the greater good: That’s Bitful
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