Senior Software Developer- Data Delivery

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  Design, build, test, and operate scalable data pipelines, data services, and data delivery workflows in a cloud environment

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  Develop and maintain analytics-ready and AI-ready datasets by creating well-structured data models, metadata, documentation, business definitions, and governed access patterns that support reporting, analytics, and future intelligence use cases

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  Contribute to technical designs for data-intensive systems with attention to performance, maintainability, resiliency, security, and cost efficiency

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  Implement production-quality code and infrastructure changes using modern software engineering practices, including automated testing, code review, CI/CD, and observability

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  Improve the quality, reliability, and scalability of data pipelines and data products through monitoring and production-readiness practices

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  Collaborate with product owners, engineering managers, architects, data consumers, and peer engineers to clarify requirements and deliver incremental value

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  Participate in technical discussions and design reviews, bringing a data engineering perspective to tradeoffs around modeling, storage, processing, and service boundaries

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  Improve team engineering standards, documentation, runbooks, and operational practices for data delivery systems

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  Mentor less-experienced engineers through pairing, design feedback, and code reviews while continuing to contribute directly to implementation

• 5+ years of professional data engineering experience

• Strong hands-on experience designing, developing, and operating production data pipelines, distributed services, or data platforms in the cloud

• Proficiency with data modeling, data architecture, data storage technologies, and transformation workflows

• Experience with batch and/or streaming data processing, event-driven systems, message queues, and resilient integration patterns

• Strong programming skills in one or more backend/data engineering languages such as Python, Java, Kotlin, Scala, TypeScript, or Go

• Practical experience with SQL and query optimization, including designing data sets for analytics, reporting, or product-facing consumption

• Good understanding of observability for data systems, including monitoring, logging, alerting, tracing, pipeline health, and data quality signals

• Ability to break down ambiguous requirements, propose pragmatic solutions, and deliver independently within a team roadmap

• Strong communication skills with the ability to explain technical tradeoffs to engineers, product managers, and engineering leaders

• Self-motivated, collaborative, empathetic, and accountable, with a bias toward ownership and continuous improvement

• Experience with AWS infrastructure, services, and tools relevant to data engineering and backend services

• Hands-on experience with data orchestration, workflow engines, lakehouse/warehouse patterns, or large-scale object storage

• Experience preparing data assets for analytics, AI/ML, LLM, or internal intelligence use cases through structured datasets, metadata, documentation, and governed access patterns

• Experience with API architecture and data access patterns for internal platforms or external product integrations

• Security knowledge and understanding of common SaaS data-handling risks and mitigation patterns

• Demonstrated ownership of production services, including incident response, post-incident learning, and operational improvements

• Strong attention to detail, especially around data correctness, edge cases, and production readiness

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