Senior Python Data Engineer: Pipelines, Quality & Monitoring

Convo; Islamabad; On-site; PKR 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Medical benefit for you and family

Free lunch

Performance-based increments

Job summary

Convo is looking for a Python Data Engineer with 3+ years of production data engineering experience. The role focuses on building and maintaining data pipelines using Python and SQL, with expertise in Airflow/Azure Data Factory, Spark, and data quality controls to ensure data freshness and reliability.

The candidate will troubleshoot pipeline issues, implement schema validation, and contribute to monitoring and incident response, collaborating with senior engineers and platform operations to

Qualifications

• Minimum experience: 3+ years in production data engineering or data-pipeline operations using Python and SQL.
• Production Python and SQL for data engineering.
• Airflow, Azure Data Factory or comparable workflow orchestration.
• Working knowledge of Spark and distributed data-processing concepts.
• Data-quality and schema-validation implementation.
• Monitoring, incident triage and root-cause analysis.

Responsibilities

• Maintain and enhance Python/SQL pipelines orchestrated through Airflow, Azure Data Factory or equivalent.
• Implement schema, completeness, freshness and reconciliation checks.
• Diagnose and resolve pipeline failures, data-quality incidents and performance regressions.
• Support Spark jobs and incremental data-processing patterns.
• Add monitoring, structured logging and actionable alerts.
• Document fixes, recurring failure patterns and operational procedures.

Skills

Python

SQL

Airflow/Azure Data Factory

Spark

Data quality

Schema validation

Monitoring

Tools

Airflow

Azure Data Factory

Databricks

Delta Lake

Job description

Convo is looking for a Python Data Engineer with 3+ years of production data engineering experience. The role focuses on building and maintaining data pipelines using Python and SQL, with expertise in Airflow/Azure Data Factory, Spark, and data quality controls to ensure data freshness and reliability.

The candidate will troubleshoot pipeline issues, implement schema validation, and contribute to monitoring and incident response, collaborating with senior engineers and platform operations to