Data Engineer

Job Summary Key Responsibilities: · Design and maintain scalable enterprise data architectures across cloud, on-premises, and hybrid environments. · Build reliable data pipelines for ETL/ELT, batch, streaming, and real-time processing. · Develop data models and standards for analytics, reporting, applications, and AI/ML use cases. · Ensure data quality, security, availability, integrity, backup, and recovery across systems. · Optimize databases, data warehouses, lakes, and analytical platforms for performance and scalability. · Monitor data platforms, troubleshoot issues, and improve reliability and efficiency. · Collaborate with AI/ML, development, infrastructure, database, analytics, and cybersecurity teams. · Maintain technical documentation and support business intelligence, integration, and data-driven decision-making. Job Requirements Required Qualifications: · Bachelor’s degree in Computer Science, Information Technology, Software Engineering, Data Science, or a related field. · Proven experience in data engineering, database development, or data infrastructure management. · Strong knowledge of SQL and relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle. · Experience designing and maintaining ETL/ELT pipelines, data integration, and data transformation processes. · Proficiency in at least one programming language commonly used in data engineering, preferably Python. · Understanding of data modeling, data warehousing, database optimization, and data quality management. · Experience with APIs, structured and unstructured data sources, and system-to-system data integration. · Knowledge of data security, access control, backup, recovery, and data protection best practices. · Familiarity with cloud or on premise data platforms, Linux environments, and version control tools such as Git. · Strong analytical, troubleshooting, documentation, communication, and teamwork skills. · Ability to collaborate effectively with AI/ML, software development, infrastructure, cybersecurity, analytics, and database teams. Preferred Qualifications: · Master’s degree in Computer Science, Data Engineering, Information Technology, Software Engineering, or a related field. · Relevant professional certifications in data engineering, databases, cloud platforms, or related technologies. · Experience with data warehousing, data lakes, ETL/ELT, and large-scale data processing. · Familiarity with cloud or hybrid data platforms such as AWS, Azure, or Google Cloud. · Knowledge of data governance, data quality, metadata management, and data security practices. Experience Requirement: · 5+ years of relevant experience in data engineering, database development, or data integration. · Practical experience in building and maintaining ETL/ELT pipelines and data workflows. · Experience with SQL databases, data modeling, and data processing. · Experience working with APIs and integrating data from multiple sources. · Experience with on premise, self-hosted, cloud, or hybrid data environments. · Experience in data quality, security, backup, recovery, and performance optimization. · Experience collaborating with AI/ML, software development, infrastructure, cybersecurity, and analytics teams. Plus, Points: · Experience with tools such as Apache Airflow, Spark, Kafka, Hadoop, or similar technologies. · Experience supporting AI/ML data pipelines and preparing data for machine learning systems. · Familiarity with Docker, Kubernetes, CI/CD, and DevOps practices. · Experience working with both on premise and cloud-based infrastructure. · Knowledge of business intelligence and reporting tools such as Power BI, Tableau, or similar platforms. · Previous experience working in telecom, technology, government, or large-scale enterprise environments. · Strong knowledge of English, Pashto, and/or Dari is an advantage.