Data Engineer

We are seeking a highly skilled and experienced professional with a Master’s degree or equivalent 16 years of education in Computer Science, Software Engineering, Data Sciences, Information Technology, or a related field from an HEC-recognized national or foreign university. The ideal candidate will have a strong background in data engineering, with at least five years of verifiable post-qualification experience in both public and private sectors. This role demands expertise in SQL, Python, and ETL frameworks such as Apache Airflow, SSIS, or Azure Data Factory. The candidate should also be proficient in data warehousing solutions and familiar with cloud platforms, alongside a solid understanding of database architecture and data modeling.

Key Responsibilities

- Design, develop, and maintain ETL pipelines using frameworks like Apache Airflow, SSIS, or Azure Data Factory to ensure efficient data processing and integration.
- Manage and optimize data warehousing solutions, including platforms such as Snowflake, Redshift, BigQuery, or Azure Synapse, to support business intelligence and analytics.
- Collaborate with cross-functional teams to implement data models and database architectures that meet organizational needs.
- Utilize SQL and Python to extract, transform, and load data, ensuring data quality and integrity throughout the process.
- Implement big data technologies like Hadoop and Spark to handle large-scale data processing tasks.
- Develop and maintain DevOps pipelines and CI/CD practices specifically tailored for data workflows to enhance deployment efficiency and reliability.
- Integrate APIs and manage real-time data streaming solutions using technologies such as Kafka or Event Hubs.
- Troubleshoot and debug data-related issues promptly to minimize downtime and maintain system performance.
- Stay updated with emerging trends and best practices in data engineering, cloud computing, and big data technologies.

Required Qualifications

- Master’s degree or 16 years of education in Computer Science, Software Engineering, Data Sciences, Information Technology, or a related discipline from an HEC-recognized institution.
- Minimum of five years of relevant post-qualification experience in data engineering roles within public or private sectors.
- Proficiency in SQL and Python programming languages.
- Hands-on experience with ETL frameworks including Apache Airflow, SSIS, or Azure Data Factory.
- Demonstrated expertise in data warehousing platforms such as Snowflake, Redshift, BigQuery, or Azure Synapse.
- Familiarity with major cloud platforms like Azure, AWS, or Google Cloud Platform (GCP).
- Strong understanding of database architecture, data modeling techniques, and best practices.
- Experience with big data ecosystems, including Hadoop and Spark.
- Knowledge of DevOps methodologies and CI/CD pipelines for data workflows.
- Experience with API integration and real-time data streaming technologies such as Kafka or Event Hubs.
- Excellent problem-solving abilities and debugging skills.

Preferred Qualifications and Benefits

While not explicitly mentioned, candidates with additional certifications in cloud platforms, big data technologies, or DevOps practices will be considered favorably. The role offers an opportunity to work with cutting-edge data engineering tools and technologies in a dynamic environment, contributing to impactful data-driven decision-making processes.

Interested candidates are encouraged to apply before the closing date of 20-Nov-2026.