Company Description PPStack is a global EdTech brand focused on transforming education, careers, and digital growth through AI-powered and technology-driven learning solutions. The company empowers students, professionals, and organizations with future-ready skills, practical training, and career acceleration programs designed for the digital era.

PPStack offers a comprehensive ecosystem that includes AI-based learning platforms, crash courses, corporate training, career coaching, digital branding, and technology consulting. By bridging the gap between education and industry, PPStack supports learners worldwide in achieving meaningful career transformation and digital empowerment. Its mission is to make learning smarter, faster, and more impactful while driving innovation in education and technology.

Role Description The ETL Specialist at PPStack is responsible for designing, developing, and maintaining robust Extract-Transform-Load processes that support the company’s data-driven EdTech and career solutions. In this full-time remote role, the specialist will build and optimize data pipelines, integrate data from multiple sources, and ensure reliable data flows into data warehouses and analytics platforms.

Day-to-day tasks include implementing ETL jobs using industry-standard ETL tools, performing data modeling to support reporting and analytics, and collaborating with engineering, product, and analytics teams to understand data requirements. The role also involves monitoring ETL performance, troubleshooting data issues,



improving data quality, and documenting workflows and technical specifications. The ETL Specialist contributes to scalable data infrastructure that enables AI-powered insights, personalized learning experiences, and operational efficiency across PPStack’s platforms.

Qualifications

- Robust proficiency in Extract Transform Load (ETL) concepts and practices, with experience designing and implementing end-to-end ETL workflows.
- Hands-on experience with ETL tools (e.g., Informatica, Talend, SSIS, Airflow, dbt, or similar platforms) for building and managing data pipelines.
- Solid understanding of data modeling techniques, including dimensional modeling and schema design for analytics and reporting.
- Experience in data integration, including working with APIs, databases, flat files, and cloud-based data sources.
- Knowledge of data warehousing principles and architectures, including star/snowflake schemas and modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift).
- Proficiency in SQL and at least one programming or scripting language commonly used for data engineering (e.g., Python).
- Familiarity with cloud platforms (such as AWS, Azure, or GCP) and related data services is beneficial.
- Understanding of data quality, data governance, and performance optimization best practices.
- Ability to work effectively in a remote, cross-functional team environment and communicate technical concepts clearly to non-technical stakeholders.

📌 ETL (India)
🏢 PPStack
📍 India