Design and implement efficient backend services and pipelines for ingesting, transforming, and processing large-scale data from multiple sources

Collaborate with Product Managers and Engineers to develop ML/AI-powered systems that generate actionable insights and automate workflows

Build APIs and internal tools to support analytics, reporting, and real-time data visualizations

Define and maintain data models, governance policies, and quality standards to uphold data integrity and accessibility across teams

Optimize data pipelines through strategies like indexing, caching, and asynchronous processing

Drive architectural decisions around event-driven systems, distributed processing, and scalable job orchestration

Improve CI/CD workflows, observability, and automation for high availability and reliability of data infrastructure

Participate in technical discussions, code reviews, and retrospective sessions to ensure continuous improvement and innovation

3+ years of experience with Python, Golang, or PHP in backend development

3+ years of experience designing and building backend platforms and services

2+ years working with data engineering tools like Airflow, dbt, Spark, or Kafka

Knowledge of relational databases (e.g., MySQL) with experience in data modeling, schema design, and performance tuning

Background in implementing ML/AI-powered solutions for large-scale data processing

Expertise in using distributed systems, message queues, or stream processing frameworks

Competency in developing APIs or services for advanced analytics and reporting

Proficiency in caching tools like Redis or Memcached and containerization technologies such as Docker

Familiarity with Linux systems and DevOps practices

Understanding of observability tools like New Relic or Datadog