Senior Software Development Engineer - Big Data
J
JobgetherBig data, AI
Work remotely from an eligible location within the United StatesFull-TimeSenior
Salary$164,400–$262,600 annually in California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington State, and Washington, D.C.; $156,200–$249,400 annually in Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia. Compensation for other eligible US locations may vary.
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Job Details
- Experience
- At least 8 years of software engineering experience
- Required Skills
- Data modelingDistributed Systems
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or an equivalent combination of education and professional experience.
- At least 8 years of software engineering experience focused on building, deploying, and operating data-intensive applications or distributed systems.
- Experience designing, implementing, and supporting production-grade data pipelines and platforms using modern big data, streaming, and/or cloud-native technologies.
- Strong understanding of scalable data processing, data modeling, storage strategies, distributed computing, system reliability, and performance optimization.
- Experience developing and maintaining reliable data services, including automated testing, monitoring, observability, alerting, and operational troubleshooting.
- Hands-on experience building agentic solutions or AI-powered capabilities using major AI tools and shared internal platforms.
- Ability to build robust services, integrations, authentication mechanisms, and APIs for scalable data and AI applications.
- Ability to collaborate with product, analytics, data science, and engineering stakeholders to deliver solutions aligned with business objectives.
- Ability to lead design discussions, conduct code reviews, mentor engineers, and promote engineering standards.
- Strong written and verbal communication skills, including explaining technical concepts and documenting architectures.
- Databricks experience is considered an advantage.
Responsibilities
- Architect, implement, and maintain secure, observable, reliable data pipelines and services for large datasets.
- Develop data models, storage strategies, and processing frameworks for high-volume, real-time, and batch workloads.
- Lead technical design reviews and code reviews, and mentor engineers on data quality, resilience, and operational excellence.
- Partner with product management, analytics, data science, and platform engineering to turn business and modeling requirements into production-grade data solutions and APIs.
- Develop and maintain shared context-layer services, agent tools, authentication mechanisms, and APIs for AI-powered applications.
- Implement automated testing, monitoring, alerting, and incident response processes to improve availability, data integrity, and performance.
- Evaluate and introduce big data technologies, development tools, and architectural patterns.
- Document data flows, system interfaces, and operational runbooks, and contribute to shared frameworks and reusable components.
- Identify opportunities to strengthen platform architecture, simplify operations, and improve distributed data systems.
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