Data Application Production Support Engineer (Telecom Background)

Job Description We are seeking a highly skilled professional to join our Data Application Production Support team. The role involves monitoring, troubleshooting, and maintaining critical data applications and pipelines in a distributed environment. The ideal candidate will have strong expertise in Python, SQL, Databricks, Unix, Azure, and distributed systems, ensuring high availability and reliability of data services.

Key Responsibilities Application Monitoring:

Proactively monitor data pipelines, jobs, and applications to ensure smooth operations.

Incident Management:

Diagnose and resolve production issues, minimizing downtime and impact.

Data Pipeline Support:

Maintain and troubleshoot ETL workflows in Databricks and other platforms.

SQL Query Optimization:

Write, debug, and optimize SQL queries for performance and accuracy.

Automation:

Develop scripts in Python to automate repetitive tasks and improve efficiency.

Unix Administration:

Manage and troubleshoot jobs running on Unix/Linux environments.

Cloud Operations:

Support and maintain applications deployed on Azure cloud infrastructure.

Distributed Systems:

Ensure reliability and scalability of applications running in distributed environments.

Collaboration:

Work closely with developers, data engineers, and business stakeholders to resolve issues and implement improvements.

Required Skills Python:

Strong scripting and automation skills.

Databricks:

Hands-on experience with Spark jobs, notebooks, and workflows.

SQL:

Advanced query writing, debugging, and optimization.

Unix/Linux:

Proficiency in shell scripting, job scheduling, and system monitoring.

Azure:

Familiarity with Azure Data Factory, storage, and cloud monitoring tools.

Distributed Systems:

Understanding of scalability, fault tolerance, and performance tuning. Preferred Qualifications Experience in production support for large-scale data applications. Knowledge of incident management tools (ServiceNow, Jira). Familiarity with CI/CD pipelines and DevOps practices. Strong problem-solving and analytical skills.