Senior Fabric Data Engineer modernizing learning - platform data for Cornerstone Galaxy. Building Microsoft Fabric pipelines, curated datasets, governance, and analytics - ready integrations.
About the role
- Staff Data Engineer building scalable pipelines and lakehouse architecture for Sonatype, a software supply chain security company. Driving trusted analytics, ML, and business intelligence data with Databricks, Spark, and modern cloud technologies.
Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT processes
- Architect and optimize data models and storage solutions for analytics and operational use
- Collaborate with data scientists, analysts, and engineers to deliver trusted, high-quality datasets
- Own and evolve parts of the data platform using Databricks and Spark
- Implement observability, alerting, and data quality monitoring for critical pipelines
- Drive data engineering best practices, including documentation, testing, and CI/CD
- Drive long-term architectural vision and mentor the team on engineering best practices
- Partner with stakeholders to ensure data solutions support business outcomes
- Contribute to the design and evolution of the next-generation data lakehouse architecture
Requirements
- 8+ years of experience as a Data Engineer or similar backend engineering role
- Bachelor’s degree in Computer Science, Engineering, or related technical field
- Databricks optimization, including tuning Spark jobs, optimizing joins, and managing Delta Lake architecture
- Experience with AI-assisted development tools and AI/ML technologies
- Strong programming skills in Python, Scala, or Java
- Hands-on experience with distributed data systems such as Spark or Kafka
- Proficiency writing and optimizing complex SQL and NoSQL queries
- Experience building and maintaining robust production ETL/ELT pipelines
- Understanding of data modeling techniques, including star schema and dimensional modeling
- Familiarity with software supply chain, cybersecurity, or large-scale software ecosystem data
- Track record improving data platform reliability, scalability, performance, and cost efficiency
- Familiarity with workflow orchestration tools such as Airflow or Dagster
- Hands-on experience with cloud data platforms, particularly AWS
- Familiarity with Delta Lake, Apache Iceberg, or Apache Hudi
- Experience implementing data observability, lineage, governance, and automated data quality frameworks
- Experience designing real-time or streaming data architectures using data lake technologies
Benefits
- Parental leave
- Diversity and inclusion working groups
- Flexible working practices
- Paid Volunteer Time Off (VTO)
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