Summary
✨ AI‑Generated
A full-time onsite Data Engineer role focused on designing, building, and maintaining scalable data pipelines and infrastructure for analytics and reporting. Responsibilities include ETL, data modeling, data warehousing, reliability and security, performance optimization, and resolving data-quality issues. The role requires close collaboration with analysts, business teams, and engineering peers.
Highlights
Full-time onsite data engineering role with responsibility for scalable data pipelines, infrastructure, modeling, and warehousing. The position offers cross-functional collaboration with analysts, business stakeholders, and engineering teams while contributing to ongoing improvements in data architecture.
Description
Role Description The Data Engineer will design, build, and maintain scalable data pipelines and infrastructure to support analytics and reporting across the organization.
Day-to-day responsibilities include implementing ETL processes, modeling data structures, and managing data warehousing solutions to ensure data is reliable, secure, and accessible for stakeholders.
The role will collaborate closely with data analysts, business teams, and engineering peers to define data requirements, optimize performance, and resolve data quality issues.
This is a full-time, on-site position based in Kathmandu, requiring regular interaction with cross-functional teams and involvement in ongoing improvements to the data architecture.
Qualifications
Candidates should possess strong Data Engineering skills, including experience building and maintaining data pipelines.Candidates should possess Data Modeling and Data Warehousing skills to design efficient, scalable data structures and storage solutions.Candidates should possess Extract Transform Load (ETL) skills to integrate data from multiple sources into consistent, usable formats.Candidates should possess Data Analytics skills to support reporting, dashboards, and data-driven decision-making.Proficiency with SQL and at least one programming language commonly used for data engineering (e.g., Python, Java, or Scala).Experience with relational and NoSQL databases, and familiarity with modern data platforms or cloud services (e.g., AWS, Azure, or GCP) is beneficial.Strong problem-solving abilities, attention to data quality, and the capacity to work collaboratively in an on-site environment.Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
