| Location | Rockville, MD (Remote) |
Title: Senior Backend Engineer – Big Data & AWS
Location: 100% remote
Target Start Date: ASAP
Type: contract
Pay Rate: DOE
We are seeking an experienced Senior Backend Engineer to design and develop scalable, high-performance backend systems supporting complex, data-intensive applications. This role offers the opportunity to contribute to a greenfield architecture initiative, building innovative solutions that enable users to efficiently access, analyze, and interact with large-scale datasets.
The ideal candidate combines strong software engineering fundamentals with deep expertise in big data technologies, AWS cloud infrastructure, and performance optimization. You will lead through technical excellence, solve complex engineering challenges, influence architectural decisions, and collaborate with cross-functional teams to deliver reliable, scalable solutions.
Design, develop, test, implement, and support scalable technical solutions within an Agile development environment.
Build distributed microservices and data-intensive applications leveraging technologies such as Hive, Presto, Spark, and Hadoop.
Develop and maintain high-performance API platforms on AWS, enabling efficient, low-latency access to large datasets.
Optimize system performance, troubleshoot bottlenecks, and ensure scalability and reliability.
Apply AWS Well-Architected Framework principles to cloud-based solutions.
Partner with cross-functional teams to understand business requirements, application needs, and testing scenarios.
Translate complex technical and business challenges into scalable, maintainable solutions.
Contribute to architecture discussions, technical design decisions, and engineering best practices.
Leverage AI-powered development tools, such as Kiro, GitHub Copilot, or similar technologies, to improve engineering productivity and code quality.
Integrate AI-assisted capabilities throughout the software development lifecycle (SDLC), including architecture, development, testing, deployment, and production support.
Evaluate emerging technologies, frameworks, and AI/ML advancements to identify opportunities for innovation.
Apply sound engineering judgment when reviewing, validating, and implementing AI-generated solutions.
Take ownership of technical deliverables from initial design through production implementation.
Establish high standards for code quality, performance, maintainability, and reliability.
Demonstrate strong problem-solving skills, sound technical judgment, and a continuous improvement mindset.
Collaborate effectively with engineering teams and stakeholders to drive successful outcomes.
3+ years of hands-on experience with big data technologies such as Hadoop, Spark, or Presto, including a strong understanding of system internals, performance tuning, and optimization.
Proven experience with AWS services, including EMR (Hive/Presto), ECS, Lambda, and S3.
Demonstrated ability to diagnose and resolve performance bottlenecks in large-scale distributed systems.
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field.
8+ years of professional software engineering experience, including demonstrated technical leadership.
3+ years of hands-on development experience with Java, JavaScript/TypeScript, or SQL.
2+ years of experience developing RESTful APIs/web services and writing complex SQL queries against relational databases.
Strong understanding of software architecture, distributed systems, and scalable application development.
Experience implementing CI/CD pipelines and DevOps practices using tools such as Jenkins and AWS CloudFormation.
Working knowledge of scripting languages, including Python or Unix Shell.
Familiarity with cloud infrastructure automation, deployment processes, and production troubleshooting.
Hands-on experience with LLM-based coding assistants, such as Kiro, GitHub Copilot, or comparable tools.
Experience applying AI-assisted development practices across the SDLC, including design, coding, testing, and deployment.
Ability to critically evaluate AI-generated code for correctness, security, performance, and maintainability.
Commitment to engineering accountability, ensuring all implemented code is thoroughly understood, reviewed, and validated.
The successful candidate is a technically strong, solutions-oriented engineer who thrives on solving complex problems involving big data, cloud architecture, and backend performance. They bring a combination of hands-on development expertise, architectural judgment, technical leadership, and enthusiasm for leveraging emerging technologies to improve software engineering outcomes.
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