Job Description: Qualification: Bachelor's or Master's degree (16 years of education) in Computer Science, Software Engineering or a related field from an HEC-recognized university. Preference would be given to foreign qualified candidates with proven track record. Experience: At least 5 years of hands-on data-engineering experience with production pipelines; government or large-enterprise integration experience preferred. Skills & Competencies: • Expert SQL and Python • Spark / Airflow / dbt / Kafka (or equivalents) • Cloud data services (AWS/Azure/GCP), Docker, Git, CI/CD • Data modelling, quality and observability • APIs (REST) and familiarity with legacy system integration Key Performance Indicators (KPIs): • Number and reliability of data pipelines built and maintained. • Data-quality, latency and pipeline-uptime metrics. Job Responsibilities: Key Responsibilities / ToRs: • Design, build and maintain batch and streaming pipelines ingesting data from departmental systems, files and APIs. • Model and manage warehouse/lakehouse schemas; implement transformations (dbt/Spark/SQL) with tests and documentation. • Develop and maintain data APIs and integrations with departmental applications and AI/ML models. • Implement data-quality checks, monitoring, alerting and incident response for pipelines. • Apply access controls, encryption, anonymization/pseudonymization as per governance standards. • Collaborate with AI/ML Engineers on feature pipelines and training/serving data flows. Last date to apply: 12-Nov-2026