Senior Software Development Engineer - Big Data

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Design and develop scalable data infrastructure: Architect, implement, and maintain secure, observable, and reliable data pipelines and services that collect, process, and store large, diverse datasets for analytics, machine learning, and product applications.

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Optimize data processing and storage: Develop efficient data models, storage strategies, and processing frameworks to support high-volume, real-time, and batch workloads while balancing performance, reliability, and infrastructure costs.

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Lead technical excellence: Drive technical design reviews, code reviews, and engineering best practices, providing guidance and mentorship to engineers on data quality, system resilience, and operational excellence.

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Collaborate across teams: Partner with product management, analytics, data science, and platform engineering teams to translate business objectives and modeling requirements into robust, production-grade data solutions and APIs.

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Build AI and agentic platform capabilities: Develop and maintain shared context-layer services, agent tools, authentication mechanisms, and APIs that enable teams across the organization to build and deploy AI-powered applications at scale.

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Ensure reliability and data quality: Implement automated testing, monitoring, alerting, and incident response processes to improve service availability, data integrity, and overall platform performance.

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Drive technology innovation: Evaluate and introduce modern big data technologies, development tools, and architectural patterns to improve developer productivity, scalability, and end-to-end data lifecycle management.

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Establish engineering standards: Document data flows, system interfaces, and operational runbooks while contributing to shared frameworks, reusable components, and best practices for big data engineering.

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Support continuous improvement: Identify opportunities to strengthen platform architecture, simplify operations, and improve the efficiency and maintainability of distributed data systems.

Requirements

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Education: Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or an equivalent combination of education and professional experience.

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Professional experience: At least 8 years of software engineering experience, with a strong focus on building, deploying, and operating data-intensive applications or distributed systems.

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Big data engineering expertise: Demonstrated experience designing, implementing, and supporting production-grade data pipelines and platforms using modern big data, streaming, and/or cloud-native technologies.

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Data architecture and systems design: Strong understanding of scalable data processing, data modeling, storage strategies, distributed computing, system reliability, and performance optimization.

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Production engineering: Experience developing and maintaining reliable data services, including automated testing, monitoring, observability, alerting, and operational troubleshooting.

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AI and agentic technologies: Hands-on experience building agentic solutions or AI-powered capabilities using major AI tools and shared internal platforms. Experience with Databricks is considered an advantage.

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API and platform development: Ability to build robust services, integrations, authentication mechanisms, and APIs that support scalable data and AI applications.

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Cross-functional collaboration: Proven ability to work effectively with product, analytics, data science, and engineering stakeholders to deliver solutions aligned with business objectives.

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Technical leadership: Strong problem-solving skills and the ability to lead design discussions, conduct code reviews, mentor engineers, and promote consistent engineering standards.

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Communication and documentation: Excellent written and verbal communication skills, with the ability to explain complex technical concepts, document architectures, and collaborate effectively across distributed teams.

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Adaptability and continuous learning: Ability to navigate evolving technologies, evaluate new tools, manage competing priorities, and continuously improve engineering practices in a fast-paced environment.

Benefits

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Competitive base salary: Compensation varies by work location:

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$164,400–$262,600 annually in California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington State, and Washington, D.C.

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$156,200–$249,400 annually in Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia.

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Compensation for other eligible US locations may vary.

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Equity awards: Eligibility for equity compensation based on factors including experience, performance, and geographic location.

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Remote work flexibility: Work remotely from an eligible location within the United States, with flexibility supported by a distributed-work model.

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Career development: Opportunities to work on large-scale data platforms, emerging AI technologies, and innovative engineering initiatives.

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Technical leadership opportunities: Influence architectural decisions, establish engineering standards, and mentor colleagues across technical teams.

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Collaborative environment: Work alongside professionals in software engineering, data science, analytics, product development, and cloud infrastructure.

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Inclusive workplace: Join an environment committed to equal employment opportunities, collaboration, innovation, and professional growth.

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