Qloo

Backend Engineer

• Building, optimizing, and maintaining backend services and APIs with a focus on performance and reliability.
• Developing and maintaining internal tools, observability systems (logging, telemetry, metrics), and data pipelines.
• Taking on varied technical challenges as priorities shift—whether that's improving CI/CD workflows, enhancing security posture, or architecting new systems.
• Collaborate closely with a cross-functional engineering team of 6–7 engineers on delivering microservices and backend infrastructure improvements.
• Contributing to infrastructure and deployment strategies using AWS and Terraform.
• Championing best practices in testing, documentation, and automation.
• Mentoring teammates and providing technical leadership for complex backend systems.

Senior Backend Engineer – Platform

Data Engineer

• Design, develop, and maintain batch data pipelines using Python, Spark (EMR), and AWS Glue, loading data from S3, RDS, and external sources into Hive/Athena tables.
• Model datasets in our S3/Hive data lake to support analytics (Hex), API use cases, Elasticsearch indexes, and ML models.
• Implement and operate workflows in Airflow (MWAA), including dependency management, scheduling, retries, and alerting via Slack.
• Build robust data quality and validation checks (schema validation, freshness/volume checks, anomaly detection) and ensure issues are surfaced quickly with monitoring and alerts.
• Optimize jobs for cost and performance (partitioning, file formats, join strategies, proper use of EMR/Glue resources).
• Collaborate closely with data scientists, ML engineers, and application engineers to understand data requirements and design schemas and pipelines that serve multiple use cases.
• Contribute to internal tooling and shared libraries that make working with our data platform faster, safer, and more consistent.
• Document pipelines, datasets, and best practices so the broader team can easily understand and work with our data.