Senior Python Data Engineer: Build Reliable Data Pipelines

Convo; Islamabad; On-site; PKR 3,000,000 - 5,400,000; Full time

Benefits offered by this job

Medical benefits

Free lunch

Performance-based raises

Lean & agile culture

Job summary

Convo is seeking a Python Data Engineer with 3+ years of production data engineering experience to own and optimize data pipelines. You will work with Python, SQL, Airflow or Azure Data Factory, Spark, and focus on data quality, schema validation, and monitoring to ensure freshness and reliability.

You will troubleshoot pipeline incidents, implement automated checks, and contribute to scalable data platforms.

Qualifications

• 3+ years of production data engineering or data-pipeline operations.
• Strong Python and SQL for data engineering.
• Experience with Airflow/Azure Data Factory or comparable.
• Knowledge of Spark and distributed data processing.
• Experience with data-quality and schema-validation.
• Experience with monitoring, incident triage and root-cause analysis.
• Version control, automated testing and controlled deployment practices.

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

Databricks

Delta Lake

Job description

Convo is seeking a Python Data Engineer with 3+ years of production data engineering experience to own and optimize data pipelines. You will work with Python, SQL, Airflow or Azure Data Factory, Spark, and focus on data quality, schema validation, and monitoring to ensure freshness and reliability.

You will troubleshoot pipeline incidents, implement automated checks, and contribute to scalable data platforms.