Senior Data Engineer

Responsibilities:
- Design, build, and optimize ETL/ELT pipelines using Databricks and Azure Data Factory to support enterprise data warehousing and analytics
- Work with stakeholders to provide access and security controls
- Support and maintain daily data processing operations (monitoring, alerting, issue resolution)
- Collaborate with analysts, data scientists, and stakeholders to understand data requirements and deliver solutions
- Provide technical guidance and mentorship to junior data engineers and other team members (including reviewing work from external consultants)
- Monitor and troubleshoot data systems (e.g., SQL databases, Databricks) for performance and reliability
- Implement data management best practices; lead initiatives to improve practices, tools, and processes
- Participate in code reviews, design discussions, and contribute to technical documentation
- Consult and lead business intelligence and analytics platforms

Minimum Requirements:
- 5+ years building and maintaining business-critical EDW and pipelines with a Bachelor’s degree
- 3+ years in data architecting/engineering with a track record delivering complex data solutions
- 3+ years Tier 1 SaaS integration work (e.g., Salesforce) or equivalent
- 3+ years working with AppDev and/or BI/AI team members
- Advanced SQL (complex queries, performance tuning/optimization, stored procedure development)
- Hands-on Azure Databricks (Spark processing, notebooks, Delta Lake)
- Hands-on Azure Data Factory (build/orchestrate/monitor ETL/ELT pipelines)
- Cloud experience (Azure preferred)
- Proficiency in Python
- Understanding of data warehousing concepts
- Strong problem-solving/communication and ability to manage multiple priorities
- Experience delivering data processing reliability

Benefits (if eligible): medical/dental/vision/prescription coverage; wellness resources; 401k/ESPP; paid time off; paid parental leave; disability benefits; additional programs.