As a Staff Data Engineer, you will play a pivotal role in building and optimizing our data infrastructure to enable robust, data-driven decision-making across the organization. You’ll work hands-on with cutting-edge technologies, lead complex projects, and collaborate with cross-functional teams to deliver scalable data solutions that meet business needs.Key Responsibilities:Data Engineering LeadershipLead the design and implementation of high-performance data pipelines and workflows using Databricks on AWS.Drive innovation and improvements in data engineering practices and processes across teams.Data Warehouse Development & OptimizationDevelop, maintain, and optimize our data warehouse architecture for performance, scalability, and reliability.Collaborate with data scientists and analysts to ensure the warehouse supports business intelligence and machine learning needs.ETL Pipeline DevelopmentDesign and build ETL processes to integrate, transform, and deliver data from multiple sources.Ensure ETL jobs are optimized for efficiency, accuracy, and timeliness.Data Quality & MonitoringImplement tools and frameworks to monitor and maintain data accuracy, consistency, and reliability.Build automated systems for detecting and resolving data quality issues.Collaboration & MentorshipPartner with cross-functional teams, including software engineers, product managers, and business stakeholders, to understand data requirements and deliver solutions.Provide technical guidance and mentorship to junior engineers to foster professional growth.System Performance & TroubleshootingContinuously monitor data platform performance, identifying and addressing bottlenecks.Act as a technical expert to resolve complex data engineering challenges.Documentation & Best PracticesCreate and maintain documentation for pipelines, processes, and system configurations.Advocate for best practices in coding standards, data governance, and security.
