Data Engineer

Kipplo is searching for enthusiastic graduates who are passionate about data, automation, and technology. As a Data Engineer, you'll work with modern data engineering tools to collect, process, validate, transform, and analyze business-critical information. You'll gain exposure to end-to-end ETL processes, database management, web data collection, and automation while contributing to projects that directly impact business decisions. Unlike traditional fresher roles that focus only on support activities, this position allows you to work on live production datasets, develop scalable data pipelines, automate repetitive processes, and collaborate with cross-functional teams including Product, Sales, and Business Intelligence. It's an ideal opportunity for candidates who want to build strong technical foundations in Python, SQL, ETL, and Cloud-ready data engineering technologies. Kipplo is a rapidly growing technology-driven organization focused on delivering high-quality data, market intelligence, and business solutions to clients across multiple industries. The company leverages advanced data engineering practices, automation tools, and modern analytics platforms to help businesses make informed decisions. With a strong emphasis on innovation, collaboration, and continuous learning, Kipplo provides fresh graduates with the opportunity to work on real business problems while gaining practical exposure to enterprise-grade technologies.

Develop and maintain scalable data pipelines using Python; Perform web data collection and data extraction from multiple sources; Clean, transform, and validate structured and unstructured datasets; Process large datasets using Pandas; Work with Parquet file formats efficiently; Query and manage databases using DuckDB and PostgreSQL; Build ETL and ELT pipelines using Airbyte; Automate repetitive workflows using Selenium; Create and maintain business contact databases; Prepare Market Intelligence Reports; Ensure high levels of data quality and integrity; Collaborate with Product, Sales, and BI teams; Document workflows and continuously improve engineering processes.

Python Programming; Pandas Library; ETL / ELT Pipelines; Airbyte; Selenium Automation; DuckDB; PostgreSQL; SQL Queries; Data Cleaning; Data Validation; Data Transformation; Data Acquisition; Web Scraping; Data Analysis; Parquet Files; Business Intelligence; Market Research; Data Quality Management; Problem Solving; Communication Skills; Team Collaboration.