Sr. Data Engineer (MLOps / Data Pipelines)

Job Description

We are looking for an experienced Senior Data Engineer to join a fast-growing geospatial analytics platform that processes satellite imagery and environmental data at scale. You will play a key role in evolving existing data pipelines into secure, scalable, and highly automated production systems.

This is an ideal opportunity for someone passionate about data engineering, MLOps, cloud infrastructure, and pipeline automation. You’ll collaborate with data scientists and engineers to optimize large-scale data processing, onboard new data sources, and implement best practices for performance, reliability, and deployment.

Responsibilities:

• Design, optimize, and maintain scalable MLOps and data pipeline infrastructure.
• Automate data ingestion, processing, and deployment workflows using modern MLOps practices.
• Operationalize machine learning pipelines and improve reliability, monitoring, and performance.
• Enhance CI/CD processes, containerized deployments, and cloud-based infrastructure.
• Evaluate and improve existing architecture for scalability, security, and cost efficiency.
• Integrate new data sources and optimize large-scale data processing workloads.
• Collaborate with cross-functional teams, mentor junior engineers, and drive engineering best practices.

Requirements:

• 5+ years of experience in MLOps, Data Engineering, or Platform Engineering.
• Strong expertise in Python and SQL (PostgreSQL preferred).
• Experience building and managing production ML/data pipelines.
• Hands-on experience with Docker, Kubernetes, CI/CD, and cloud platforms.
• Experience with workflow orchestration tools such as Airflow, Kafka, dbt, or similar technologies.
• Strong understanding of data lifecycle management, pipeline automation, and cloud infrastructure.
• Excellent problem-solving, communication, and collaboration skills.
• Experience with GIS, satellite imagery, PostGIS, Google Earth Engine, or geospatial data processing.
• Knowledge of orchestration and streaming tools such as Airflow, Kafka, dbt, or similar technologies.
• Experience working with large-scale datasets and distributed data processing.
• Familiarity with Redis and event-driven architectures.
• Previous experience working with international or distributed engineering teams.

Company Benefits:

• Friendly, competitive, and creative work environment with exposure to international leadership.
• Opportunity to collaborate with global teams and gain international project experience.
• Competitive salary aligned with market standards, with regular performance reviews and performance-based bonuses.
• Standard 5-day work week (9:00 AM – 5:30 PM) in a collaborative hybrid working environment.
• Access to paid learning platforms (e.g., Udemy) and exposure to modern technologies.
• Employee benefits including Provident Fund (PF), CIT, paid leave, and sick leave.
• Refreshments, recreational activities, and regular team-building events.

For more jobs, visit: www.tekkon.com.np/jobs