POSITION:
Reporting to the Manager, Software Engineering, we are seeking a highly skilled Developer to join our team and build scalable, secure, and high-performing applications. This role involves working across front-end and back-end systems, leveraging modern frameworks, cloud platforms, and data engineering tools to deliver exceptional user experiences and robust solutions.
RESPONSIBILITES:
Development & Architecture
- Design and implement client-side and server-side applications using ReactJS, Next.js, TypeScript, and Python frameworks (FastAPI, Flask, Django, AsyncIO).
- Develop backend services and APIs (REST & GraphQL) with Node.js and Python.
- Implement asynchronous programming for high-performance APIs.
- Work with SQL (Snowflake, PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Redis) databases.
- Build and maintain data pipelines using PySpark, Pandas, NumPy, and streaming systems like Apache Kafka, RabbitMQ.
- Deploy applications on AWS (EC2, Lambda, ECS, S3, CloudFront) and manage containerized workloads using Docker and Kubernetes (Helm, Operators).
- Implement CI/CD pipelines with GitHub Actions, Jenkins, ArgoCD.
- Ensure application security and compliance (GDPR, HIPAA) using tools like Vault, AWS Cognito, Let鈥檚 Encrypt.
- Monitor and troubleshoot using Prometheus, Grafana, Loki, Jaeger, OpenTelemetry.
- Optimize performance through caching strategies, load balancing, and scalable architecture.
Collaboration & Quality
- Work closely with product managers and cross-functional teams to deliver software solutions.
- Participate in agile development processes including design, implementation, and deployment.
- Write technical documentation and contribute to end-user guides.
- Conduct unit and integration testing to ensure reliability and efficiency.
REQUIREMENTS:
- 2+ years of experience as a developer.
- Strong proficiency in Python, JavaScript/TypeScript, and frameworks like FastAPI, Flask, Django, ReactJS, Next.js, Node.js.
- Hands-on experience with data engineering tools (PySpark, Pandas) and streaming platforms (Kafka, RabbitMQ).
- Expertise in AWS services (EC2, Lambda, ECS, S3, CloudFront, RDS, ElastiCache, OpenSearch) and familiarity with GCP (BigQuery, Pub/Sub) and Azure (Data Factory, Synapse Analytics).
- Knowledge of containerization and orchestration (Docker, Kubernetes) and CI/CD tools (ArgoCD, Jenkins, GitHub Actions).
- Experience with monitoring and observability tools (Prometheus, Grafana, Loki, Jaeger).
- Working experience with big data technologies (Spark) and ETL frameworks (Airflow, dbt).
- Exposure to ML/AI frameworks (Scikit-learn, TensorFlow, PyTorch) and MLOps tools (MLflow, Kubeflow).
- Strong understanding of API design, data governance, and security best practices.
- Excellent problem-solving skills, attention to detail, and ability to manage multiple priorities.