Senior Software Engineer - Trusted Data Platform

loud infrastructure. You will be responsible for developing distributed storage systems, APIs, and backend services that power mission-critical applications, ensuring low-latency, high-throughput, and fault-tolerant data storage. Your work will directly impact system reliability, scalability, and cost efficiency.

You will collaborate closely with principal engineers, architects, SREs, and product teams to define technical roadmaps, improve storage efficiency, and optimize access patterns. You will drive performance tuning, data modeling, caching strategies, and cost optimization across AWS storage services like S3, DynamoDB, EBS, EFS, FSx, and Glacier. Additionally, you will contribute to infrastructure automation, security best practices, and monitoring strategies using tools like Terraform, CloudWatch, Prometheus, and OpenTelemetry.

In this role, you will also be responsible for troubleshooting and resolving production incidents related to data integrity, latency spikes, and storage failures, ensuring high availability and disaster recovery preparedness. You will mentor junior engineers, participate in design reviews and architectural discussions, and advocate for engineering best practices such as CI/CD automation, infrastructure as code, and observability-driven development. Your contributions will directly impact the organization's ability to scale its storage infrastructure efficiently while maintaining security, reliability, and compliance with industry standards.

Basic Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.

• 5+ years of experience in backend software development.

• 3+ years of hands-on experience working with AWS cloud services, particularly AWS storage technologies (S3, DynamoDB, EBS, EFS, FSx, or Glacier).

• 3+ years of experience in designing and developing distributed systems or high-scale backend services.

• Strong programming skills in Kotlin

• Experience working in agile environments following DevOps and CI/CD best practices.

Core Requirements

1. Strong Backend Development Skills

   • Proficiency in Kotlin, Java for backend development.
   • Experience building high-performance, scalable microservices and APIs.
   • Strong understanding of RESTful APIs, gRPC, and event-driven architectures.

2. Experience with AWS Storage Technologies

   • Hands-on experience with AWS S3, DynamoDB, EBS, EFS, FSx, and Glacier.
   • Knowledge of AWS IAM, KMS, and data access policies for secure storage solutions.
   • Understanding of AWS networking (VPC, PrivateLink, Route 53) for optimizing storage performance.

3. Distributed Systems & Scalability

   • Solid understanding of distributed databases, storage consistency models, and caching mechanisms.
   • Experience with sharding, partitioning, and load balancing to scale storage-heavy applications.
   • Familiarity with event-driven architectures using AWS SNS, SQS, Kinesis, or Kafka.

4. Performance Optimization & Cost Efficiency

   • Ability to profile and optimize storage performance, indexing strategies, and data retrieval latencies.
   • Experience with cost-efficient storage solutions by implementing tiering, lifecycle policies, and data deduplication.
   • Knowledge of benchmarking and monitoring tools (CloudWatch, OpenTelemetry, Prometheus, Grafana).

5. Security & Reliability

   • Experience implementing data encryption at rest and in transit using AWS KMS or TLS.
   • Understanding of access control mechanisms (IAM roles, STS, fine-grained permissions).
   • Experience ensuring high availability and disaster recovery using AWS backup strategies and multi-region replication.

6. Hands-On with Infrastructure as Code (IaC) & DevOps

   • Experience using Terraform, AWS CloudFormation, or CDK to manage infrastructure.
   • Familiarity with CI/CD pipelines for backend deployments using GitHub Actions, CodePipeline, or Jenkins.
   • Experience with containerized deployments using Docker, Kubernetes (EKS), and serverless solutions (Lambda, Fargate).

7. Troubleshooting & Production Support

   • Strong debugging skills for investigating storage failures, high-latency issues, and API bottlenecks.
   • Experience using observability and tracing tools to monitor storage workloads.
   • Ability to triage and resolve production incidents in large-scale backend systems.

8. Collaboration & Engineering Best Practices

   • Strong experience in code reviews, unit testing, and API contract enforcement.
   • Ability to work cross-functionally with SREs, data engineers, and infrastructure teams.
   • Good documentation habits for ensuring architecture decisions and design patterns are well-documented.