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 #J-18808-Ljbffr