Explore a dynamic and critical career path at the intersection of data operations and engineering leadership with Data Engineering Support Engineer/Manager jobs. This hybrid role is essential for organizations that rely on robust, high-availability data platforms, serving as the vital bridge between data infrastructure and its business users. Professionals in this field ensure the continuous health, performance, and reliability of data pipelines and analytics systems, acting as the frontline for operational excellence. Typically, a Data Engineering Support Engineer/Manager is responsible for the entire lifecycle of data platform support. This begins with proactive monitoring and rapid incident management, diagnosing and resolving issues that impact data availability or quality. A core function involves developing and maintaining data quality frameworks, implementing checks, and anomaly detection to ensure the integrity of data consumed by analysts, scientists, and business leaders. These roles often require writing and applying hotfixes using Python and SQL to address immediate problems, while also collaborating with core data engineering teams on deeper, systemic solutions. A significant portion of the work is dedicated to automation—building diagnostic tools, scripting routine tasks, and streamlining operational processes to reduce manual toil and prevent future incidents. Beyond technical troubleshooting, this position demands strong managerial and collaborative skills, especially as it progresses into a manager-level capacity. Individuals frequently act as a central hub, working closely with cross-functional teams including data engineers, data scientists, platform engineers, and business stakeholders like analysts. They translate user-reported issues into technical action items and communicate system status and resolutions clearly. Responsibilities often extend to user management, access control, and providing direct support to end-users to resolve their data-related queries and problems efficiently. The typical skill set for these jobs is a blend of deep technical expertise and soft skills. Proficiency in programming languages like Python and SQL is fundamental, alongside a strong familiarity with data engineering concepts, ETL/ELT processes, and data modeling. Experience with cloud data services (such as those from AWS, Azure, or GCP) is highly common. Equally important are exceptional problem-solving abilities, a methodical approach to debugging, and outstanding communication skills. The role requires someone who can organize and prioritize a fluctuating workload, manage stakeholder expectations, and lead initiatives to improve system reliability. For those seeking Data Engineering Support Engineer/Manager jobs, a background in computer science or engineering is typical, with successful candidates demonstrating a passion for operational stability, continuous improvement, and enabling data-driven decision-making across the enterprise.
