Our Client, a multinational telecommunications technology company has an urgent and immediate need for an experienced Data Application Production Support Engineer. The role involves monitoring, troubleshooting, and maintaining critical data applications and pipelines in a distributed environment.

We're seeking candidates with 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.

If you would like to learn more, please reach out to Elite Technical.

Required Skills

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.
- Strong problem-solving and analytical skills.

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.