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Jobs(38,923)/Senior Data Engineer Role(360)/Deduction (2) - Senior Data Engineer
Deduction

Deduction - Senior Data Engineer

Remote - United States1mo ago
RemoteSeniorNAFintechArtificial IntelligenceSenior Data EngineerSoftware EngineerTypeScriptPython

Requirements

• Proven experience owning and operating data-heavy systems in production • data-heavy systems in production • Strong experience with data pipelines (ETL/ELT, event-driven, or workflow-based systems) • data pipelines • Proficiency in TypeScript (primary language); other typed language experience is a plus • TypeScript • other typed language • Generalist mindset with strong data modeling and system design instincts • strong data modeling and system design instincts • Ability to go from zero → one → scale with minimal guidance • zero → one → scale • Experience in fintech, tax, or regulated environments a strong plus. • fintech, tax, or regulated environments • Familiarity with security and compliance considerations (sensitive data, auditability, access controls) a strong plus. • security and compliance considerations • AI-Native Development • You actively use AI tools as a core part of your development workflow (not optional) • AI tools as a core part of your development workflow • You believe the software engineer’s job is fundamentally changing—and you lean into that shift • lean into that shift

Responsibilities

• Turn ambiguous product and operational workflows into well-structured systems combining data pipelines, backend services, and AI-driven logic • Design and build agentic AI systems that reason, take actions, and orchestrate multi-step workflows (not just simple LLM integrations) • Develop and operate production-grade data pipelines powering both user-facing features and internal systems • Build backend services primarily in TypeScript, with pragmatic use of Python where appropriate • Design APIs and system boundaries that enable modular, composable AI and data workflows • Partner with product and operations to translate real-world processes into AI-augmented, scalable systems • Use AI-assisted development as a default—from prototyping to debugging to system design • Improve reliability, observability, and performance across services • Own architectural decisions within your domain, balancing speed and long-term maintainability

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