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

• 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 App Dev 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

• medical/dental/vision/prescription coverage
• wellness resources
• 401k/ESPP
• paid time off
• paid parental leave
• disability benefits
• additional programs