Principal Software Engineer, Trusted Data Platform

As a Principal Software Engineer, you will be a technical leader and hands-on contributor, designing and optimizing high-scale, distributed storage systems built on AWS storage technologies. You will play a pivotal role in shaping the architecture, performance, and reliability of backend storage solutions that power critical applications at scale.

Your primary responsibilities will include designing, implementing, and optimizing backend storage services that support high throughput, low latency, and fault tolerance. You will work closely with senior engineers, architects, and cross-functional teams to drive scalability, availability, and efficiency improvements in large-scale storage solutions. You will also lead technical deep dives, architecture reviews, and root cause analyses to resolve complex production issues related to storage performance, consistency, and durability.

As a thought leader, you will drive best practices in distributed system design, security, and cloud cost optimization. You will also mentor senior engineers, contribute to technical roadmaps, and help shape the long-term storage strategy. Your expertise in storage consistency models, data partitioning, indexing, and caching strategies will be instrumental in improving system performance and reliability.

Additionally, you will collaborate with Site Reliability Engineers (SREs) to implement observability, monitoring, and disaster recovery strategies, ensuring high availability and compliance with industry standards. You will advocate for automation, Infrastructure-as-Code (IaC), and DevOps best practices, leveraging tools like Terraform, AWS CloudFormation, Kubernetes (EKS), and CI/CD pipelines to enable scalable deployments and operational excellence.

Basic Requirements

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

• 8+ years of experience in backend software development, focusing on distributed systems and storage solutions.

• 5+ years of experience working with AWS storage services (S3, DynamoDB, EBS, EFS, FSx, Glacier).

• Strong expertise in system design, architecture, and scalability for large-scale storage solutions.

• Proficiency in at least one major backend programming language (Kotlin, Java, Go, Rust, or Python).

• Experience designing and implementing highly available, fault-tolerant, and cost-efficient storage architectures.

• Deep understanding of distributed systems, replication strategies, sharding, and caching.

• Knowledge of data security, encryption best practices, and compliance requirements (SOC2, GDPR, HIPAA).

• Experience leading engineering teams, mentoring senior engineers, and driving technical roadmaps.

• Proficiency with observability tools, performance monitoring, and troubleshooting at scale.

Core Requirements

Expertise in Large-Scale Storage Systems

• Deep knowledge of AWS storage services (S3, DynamoDB, EBS, EFS, FSx, Glacier) and their performance characteristics.

• Experience designing and optimizing object storage, block storage, and file storage solutions at scale.

• Strong understanding of storage durability, consistency models, replication, and erasure coding for fault tolerance.

• Experience implementing tiered storage solutions and cost-optimized data retention strategies.

Distributed Systems & Scalability

• Deep understanding of distributed storage architectures, CAP theorem, and consistency models.

• Expertise in partitioning, sharding, and replication strategies for low-latency, high-throughput storage.

• Experience designing and implementing highly available, fault-tolerant distributed systems using consensus algorithms (Raft, Paxos, Gossip Protocol).

• Hands-on experience with high-performance NoSQL databases (DynamoDB, Cassandra, RocksDB).

High-Performance Backend Engineering

• Strong programming skills in Kotlin, Java, Go, Rust, or Python for backend storage development.

• Experience building event-driven, microservices-based architectures using gRPC, REST, or WebSockets.

• Expertise in data serialization formats (Parquet, Avro, ORC) for optimized storage access.

• Experience implementing data compression, deduplication, and indexing strategies to improve storage efficiency.

Cloud-Native & Infrastructure Automation

• Strong hands-on experience with AWS Well-Architected Framework and cloud storage best practices.

• Proficiency in Infrastructure as Code (IaC) using Terraform, AWS CDK, or CloudFormation.

• Experience with Kubernetes (EKS), serverless architectures (Lambda, Fargate), and containerized storage workloads.

• Expertise in CI/CD automation for storage services, leveraging GitHub Actions, CodePipeline, Jenkins, or ArgoCD.

Performance Optimization & Observability

• Experience with benchmarking, profiling, and optimizing storage workloads.

• Proficiency in performance monitoring tools (CloudWatch, Prometheus, OpenTelemetry, Grafana) for storage systems.

• Strong debugging and troubleshooting skills for latency bottlenecks, memory leaks, and concurrency issues.

• Experience designing observability strategies (tracing, metrics, structured logging) for large-scale storage systems.

Security, Compliance, and Data Protection

• Deep knowledge of data security, encryption at rest/in transit, and IAM policies in AWS.

• Experience implementing fine-grained access controls (IAM, KMS, STS, VPC Security Groups) for multi-tenant storage solutions.

• Familiarity with compliance frameworks (SOC2, GDPR, HIPAA, FedRAMP) and best practices for secure data storage.

• Expertise in disaster recovery, backup strategies, and multi-region failover solutions.

Leadership & Architectural Strategy

• Proven ability to design, document, and drive large-scale storage architectures from concept to production.

• Experience leading technical design reviews, architecture discussions, and engineering best practices.

• Strong ability to mentor senior and mid-level engineers, fostering growth in distributed storage expertise.

• Ability to influence technical roadmaps, long-term vision, and cost optimization strategies for backend storage.