Job Details

This role is categorized as hybrid. This means the successful candidate is expected to report onsite at the Austin, TX, Warren, MI, or Roswell, GA three times per week, at minimum or other frequency dictated by the business.The RoleAs a Staff Cloud Data Engineer, you will play a critical role in architecting, designing, and delivering scalable, high-performance data solutions in the cloud. You will lead the development of systems that support efficient data processing, storage, and retrieval. This is a senior-level role that requires deep technical expertise, strong leadership, and a demonstrated history of executing complex data engineering initiatives.In addition to strong data engineering capabilities, a solid foundation in software engineering principles—such as code quality, design patterns, testing, and CI/CD—is highly valued. The ideal candidate combines a data-driven mindset with modern software engineering best practices to build robust, maintainable, and production-ready data systems.Prospective team member possesses a high degree of business insight, creativity, decision making skills, a drive for results, the ability to negotiate, the ability to develop strong peer relationships, and a strong technical learning capability and focus.Your Skills & Abilities (Required Qualifications)Bachelor's Degree in Computer Science, Engineering, or equivalent degreeOver 10 years of experience in building, operating scalable and reliable platforms.Expertise leading Agile (scrum and feature driven development) teams that have regularly (daily + weekly) delivered software while practicing code reviewsDevelop data models and schemas that support efficient data storage, retrieval, and analytics, employing optimization techniques to enhance query performance and scalabilityExpertise in SQL (relational databases), key-value datastores, and document storesCreating self-contained, reusable, and testable modules and components in frontend and backend workLeverage big data technologies and frameworks (e.g., Hadoop, Spark, Hive) to process and analyze large volumes of data, enabling advanced analytics and machine learning initiatives.Manage and optimize data infrastructure, including cloud-based platforms, containerization technologies, and distributed computing environments.Ensure the security and privacy of our data and compliance with relevant regulations.Evaluate new technologies and tools for data processing, storage, and retrieval and recommend solutions to improve the efficiency and scalability of our data infrastructure.Strong proficiency in data engineering technologies, such as ETL frameworks, big data processing, and SQL and NoSQL databases.Excellent verbal and written communication skills and ability to effectively communicate and translate feedback, needs and solutionsCreative problem-solving skills that deliver elegant solutions to complex issuesStrong understanding of distributed systems and the modern data stackExperience with Databricks or snowflake and Azure/GCP platformsExperience using Git source control doing rebases, merges, and handling merge conflictsExperience in enterprise integration, common integration patterns (batch, micro-batch, near real-time and real time) and ETL toolsKnowledge of cloud-native architecture and best practicesDemonstrated knowledge and implementation experience of Data Streaming architecturesDefine, document, and maintain architecture patterns#J-18808-Ljbffr