Senior Data Engineer: Pipeline Modernization & Security

Datamatics Technologies; Islamabad; Hybrid; PKR 25,431,000 - 36,734,000; Full time

Job summary

Datamatics Technologies in Stockholm, Sweden, seeks an experienced Senior Data Engineer / Data Pipeline Architect for a 6‑month hybrid assignment. You will lead the architectural migration of critical data pipelines, while ensuring outputs remain unchanged and security requirements are met.

The role combines hands‑on development with mentoring of a Data Engineer, using Airflow, Spark, dbt, BigQuery and Python, and requires 5–10 years of experience.

Qualifications

• Minimum 5 years of relevant professional experience.
• Deep hands-on experience with Airflow, Spark, dbt, BigQuery, and Python.
• Proven experience technically leading at least one complete data pipeline migration.
• Experience refactoring production data pipelines while ensuring unchanged outputs.
• Experience establishing and implementing engineering processes for testing, code reviews, and incident management.
• Mentoring experience with measurable outcomes.

Responsibilities

• Design and drive the architecture, migrating pipelines incrementally while ensuring existing outputs remain unchanged.
• Establish sustainable engineering processes for testing, code reviews, incident management, and releases.
• Combine architectural leadership with hands-on engineering using Airflow, Spark, dbt, BigQuery, and Python.
• Collaborate closely with and mentor a Data Engineer within the team, ensuring long-term ownership and reliability.

Skills

Airflow

Spark

dbt

BigQuery

Python

Mentoring

Leadership

Data pipelines

Education

Bachelor's degree

Tools

Airflow

Spark

dbt

BigQuery

Python

Job description

Datamatics Technologies in Stockholm, Sweden, seeks an experienced Senior Data Engineer / Data Pipeline Architect for a 6‑month hybrid assignment. You will lead the architectural migration of critical data pipelines, while ensuring outputs remain unchanged and security requirements are met.

The role combines hands‑on development with mentoring of a Data Engineer, using Airflow, Spark, dbt, BigQuery and Python, and requires 5–10 years of experience.