We are seeking a hands-on and detail-oriented Data Support Engineer to support, monitor, and maintain our data platforms and ETL pipelines. This role includes managing production data operations, troubleshooting technical issues, and supporting infrastructure-level tasks such as scaling applications, modifying cluster configurations, and optimizing resources for performance and cost.

Responsibilities:

Monitor, manage, and maintain data pipelines to ensure reliable and timely data processing.

Investigate and resolve production issues and data anomalies in a timely manner, ensuring minimal business disruption.

Triage and resolve support tickets related to data functionality, job failures, performance issues, and availability.

Troubleshoot technical problems and respond to customer or internal team queries within defined SLA timelines.

Perform root cause analysis for incidents and recommend/implement long-term solutions and preventive measures.

Scale up/down infrastructure components such as Databricks clusters and Azure Data Factory integration runtimes based on pipeline needs.

Modify and manage configuration settings for performance tuning, cost optimization, and capacity planning.

Implement and execute data imports/exports for internal users or customers as needed.

Maintain and update support documentation, standard operating procedures (SOPs), and knowledge base articles.

Detect and resolve potential issues proactively before they impact the platform or downstream users.

Collaborate with engineering teams on infrastructure and platform improvements to enhance data reliability and scalability.

Requirements & Skills:

At least 3 years of experience in ETL development, production monitoring, or technical support roles.

Practical knowledge of Databricks, Azure Data Factory (ADF), Python, and SQL.

Experience working with cloud infrastructure related to data platforms, especially in Azure.

Familiarity with scaling and configuration management of cloud-based compute resources (e.g., Databricks clusters, ADF IR).

Proficiency in scripting languages (e.g., Python, Bash) for automation and data handling.

Understanding of database systems, data modeling, and data validation techniques.

Experience with data integration and ETL workflows in production environments.

Knowledge of data backup, recovery, and incident management processes.

Strong analytical and problem-solving skills for diagnosing complex technical issues.

High attention to detail and a commitment to data quality and operational excellence.

Excellent verbal and written communication skills, with a collaborative approach to teamwork.

Preferred Qualifications:

Familiarity with monitoring and alerting tools (e.g., Azure Monitor, Log Analytics).

Understanding of CI/CD practices, version control (Git), and DevOps collaboration.

Exposure to data governance, compliance, and data security best practices.

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Data Support Engineer