Data Engineer

Company Description PPStack is a global EdTech brand dedicated to reimagining the future of education by empowering learners, professionals, and organizations with future-ready digital skills. Through AI-powered learning platforms, crash courses, corporate training, and career acceleration programs, PPStack bridges the gap between education and industry. The company focuses on digital empowerment, career transformation, and technology innovation, offering solutions across AI, data, cloud, and modern software disciplines. PPStack also delivers services such as career coaching, digital branding, technology consulting, and e-learning platform development to support holistic growth. Learners worldwide trust PPStack’s ecosystem, where education drives innovation and long-term career success.
Role Description This full-time remote Data Engineer role focuses on designing, building, and maintaining scalable data solutions that power PPStack’s learning platforms, analytics, and AI-driven services. The Data Engineer will develop and optimize data pipelines and ETL processes, integrate data from multiple sources, and ensure data quality, reliability, and security across production systems. Day-to-day responsibilities include implementing data models and warehousing structures, collaborating with data analysts, data scientists, and product teams to support reporting and experimentation, and improving performance of data workflows. The role also involves monitoring data infrastructure, troubleshooting issues, documenting data assets and processes, and contributing to best practices in data engineering and governance.
Qualifications
Strong data engineering skills, including experience building and maintaining data pipelines and working with modern data platforms.
Proficiency in data modeling and designing scalable, reliable schemas for analytical and operational workloads.
Hands-on experience with Extract Transform Load (ETL) tools and frameworks, and the ability to optimize ETL/ELT workflows.
Knowledge of data warehousing concepts and implementation using cloud or on-premise data warehouse technologies.
Applied data analytics skills, including querying large datasets, generating insights, and supporting business intelligence needs.
Experience with SQL and at least one programming language commonly used in data engineering (e.g., Python, Java, or Scala).
Familiarity with cloud data services (e.g., AWS, Azure, GCP), distributed processing (e.g., Spark), and workflow orchestration tools.
Understanding of data governance, security, and compliance best practices in handling sensitive and large-scale data.
Ability to work independently in a remote environment, collaborate across diverse teams, and communicate technical concepts clearly.
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.

Work arrangement
No