Clinical Data Ops

The Clinical Data Ops role at Saama Technologies Inc involves monitoring and maintaining data ingestion, transformation, and ETL/ELT pipelines. Key responsibilities include incident management, triaging production job failures, and utilizing Unix/Linux commands for system operations. The role also focuses on data quality, performing integrity checks, and investigating discrepancies using SQL queries to support engineering teams with Root Cause Analysis.

Must Have

• Actively monitor scheduled data ingestion, transformation, and ETL/ELT pipelines.
• Ensure all jobs are tracked and status updates are provided to stakeholders.
• Identify production job failures, data delays, and processing bottlenecks.
• Perform initial triage and escalate issues to L3/Development teams for code fixes and permanent resolution.
• Utilize basic Unix/Linux commands (e.g., grep, tail, vi) to monitor server health, review log files, and restart non-critical processes.
• Perform routine checks on data quality, volume, and freshness to identify anomalies or deviations.
• Write and execute basic SQL queries (SELECT, JOINs, etc.) to investigate data discrepancies.
• Provide Root Cause Analysis (RCA) data points to the engineering team.

Description

1. Production Monitoring and Maintenance

Job Monitoring: Actively monitor scheduled data ingestion, transformation, and ETL/ELT pipelines. Ensure all jobs are tracked and status updates are provided to stakeholders.

Incident Management & Triage: Identify production job failures, data delays, and processing bottlenecks. Perform initial triage and escalate issues to the L3/Development teams for code fixes and permanent resolution.

System Operations: Utilize basic Unix/Linux commands (e.g., grep, tail, vi) to monitor server health, review log files, and restart non-critical processes as needed.

2. Data Quality and Investigation

Data Integrity Checks: Perform routine checks on data quality, volume, and freshness to identify anomalies or deviations.

SQL Investigation: Write and execute basic SQL queries (SELECT, JOINs, etc.) to investigate data discrepancies and provide Root Cause Analysis (RCA) data points to the engineering team.