Senior Software Engineer – Backend (Python / Typescript / Big Data / AWS / Kubernetes)

Posted about 1 hour agoViewed
US, CanadaFull-TimeSoftware Development
Location:US, Canada, EST
Languages:English
Seniority level:Senior, 7+ years
Experience:7+ years
Skills:
AWSBackend DevelopmentNode.jsPythonDynamoDBKafkaKubernetesSoftware ArchitectureTypeScriptREST APISparkCI/CDMentoringDevOpsTerraformMicroservices
Requirements:
7+ years of backend or full-stack engineering experience with a strong backend focus. 7+ years of hands-on Python experience (APIs, automation, large-scale data pipelines). 3+ years working with Typescript / Node.js. Advanced experience with AWS (EC2, EKS, Lambda, S3, DynamoDB, RDS, Step Functions, etc.). Strong practical experience deploying and optimizing production workloads on Kubernetes. Proven experience working with large datasets, distributed computing, and batch or stream processing using Spark, Dask, EMR, Glue, Kafka, etc. Solid understanding of system design, distributed systems, scalability patterns, and cloud architecture. Strong business-level English proficiency to communicate effectively with cross-functional teams across regions. Ability to collaborate, document solutions clearly, and participate in technical discussions with stakeholders.
Responsibilities:
Design, build, and scale new features for REST APIs and large-scale data processing pipelines that handle high-volume datasets across distributed systems. Architect and optimize backend services for high throughput and low-latency performance. Develop data-intensive and event-driven applications using Python, Typescript, Spark, and AWS-native services. Work with Spark, EMR, Glue, Kafka, or similar frameworks to process and transform very large datasets. Improve system performance, reliability, and scalability across microservices and cloud infrastructure. Partner with senior engineers, architects, DevOps, and QA throughout the full development lifecycle. Mentor developers, guide code reviews, and raise engineering quality standards. Automate deployments and CI/CD using Terraform, Serverless Framework, and Kubernetes-based workflows.
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