What are the responsibilities and job description for the Data Application Production Support Engineer (Telecom Background) position at AgreeYa Solutions?
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.