Quilt Software is looking for a Senior Data Engineer to design, build, and optimize their data platforms so teams across the company can make fast, reliable, data-driven decisions. The goal is to build scalable data solutions that power analytics, reporting, and data products.
Requirements
- Strong hands-on experience with Databricks (or a very similar cloud data platform) including cluster management, jobs, and notebooks.
- Advanced experience with Apache Spark for batch and/or streaming data processing.
- Expert-level SQL skills (complex joins, window functions, query optimization).
- Strong Python skills for data engineering (e.g., PySpark, data processing libraries, scripting).
- Proven experience in data modeling and designing schemas for analytics and reporting.
- Experience building and maintaining data pipelines in a cloud environment (AWS, Azure, or GCP).
- Strong understanding of data warehousing concepts, ETL/ELT best practices, and data lifecycle.
Responsibilities
- Design and build data pipelines
- Develop, maintain, and optimize ETL/ELT pipelines on Databricks and Spark.
- Integrate data from multiple internal and external sources into a centralized data platform.
- Design and maintain robust data models (e.g., star/snowflake schemas, data vault, dimensional models) to support analytics and self-service BI.
- Implement data quality checks, validation frameworks, and monitoring.
- Tune queries and jobs for performance and cost efficiency in Databricks and downstream systems.
- Contribute to and refine our data governance, security, and access control practices.
Other
- 7+ years of professional experience as a Data Engineer, Software Engineer, or similar role.
- Excellent communication skills and the ability to collaborate with technical and non-technical stakeholders.
- A product mindset: you think about the end users of data and build with usability in mind.
- A bias for automation, reliability, and scalability over one-off solutions.
- Comfort with ambiguity, ownership of complex problems, and a desire to continuously improve the data ecosystem.
