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Senior/Staff Software Engineer

Turing

Experience Level: Senior–Staff (8–14 years) Role Overview: We are looking for a strong software engineer who is a highly capable Python/C++ engineer with deep, hands-on production experience who also brings a specialized skill: automating desktop Microsoft Excel and its COM/VSTO add-ins as a reliable server workload. You will help build a server-side Excel execution engine for a Fortune 500 financial-services client — opening macro-heavy, add-in-dependent valuation workbooks programmatically on Windows, letting proprietary and third-party add-ins (e.g., Capital IQ) recalculate, capturing results, and safely versioning them back to cloud storage The ideal candidate is a strong engineer who can own services, integrations, and reliability engineering end to end — and who has genuinely wrestled real Excel + COM add-ins into a dependable, scaled pipeline. Key Responsibilities: Design, build, and operate production-grade backend services in Python — clean, tested, observable, and maintainable. Own Excel execution engine: open workbooks, resolve add-ins, invoke an approved action, recalculate, and capture structured output with provenance. Design interactive, session-isolated Windows/Excel workers and Preserve add-in behavior— real desktop sessions, which the COM add-ins require — and keep each run cleanly separated from the others. Orchestrate the worker pool: distribute runs across many Excel workers with queues, scheduling, retries, and idempotency, so hundreds of workbooks flow through reliably and with built-in failure recovery Validate outputs: confirm each run produced a complete, well-formed result (expected sheets/values present, no error states, integrity/hash checks) before it is trusted or written back. Engineer for capacity: size and tune the worker pool to process the full workbook volume within the monthly-close window — concurrency limits, load/soak testing, and throughput/bottleneck analysis. Contribute across the stack — system integration, debugging, performance optimization in a legacy-and-modern environment. Collaborate with the Solution Architect on boundaries and with DevOps on VM imaging, scaling, and deployment; document and transfer knowledge. Required Technical Skills: 8–13 years of professional software engineering with strong Python skills. Proven track record building and operating complex production backend services and APIs — reusable components, testing, error handling, performance, and observability. Strong engineering fundamentals: concurrency, data structures, debugging, and pragmatic performance optimization. Comfortable across the stack and across technologies — storage, queues, cloud, CI/CD — and navigating both legacy and modern systems. Ownership mindset: takes capability from design through production reliability and support. Deep hands-on experience automating desktop Excel via COM / Office interop, including interactive session design for running Office unattended on Windows servers. Running macro-heavy workbooks and third-party COM/Office add-ins programmatically: recalculation, add-in authentication/licensing, and preserving add-in behavior server-side. Experience making a normally unreliable stack dependable — failure recovery (hang/crash detection, restart, dialog handling), output validation, and capacity/throughput engineering for concurrent runs. We ARE looking for engineers who: Are excellent Python/backend engineers who build enterprise grade production systems well, and Have real, demonstrable server-side Excel + COM add-in automation experience, and Good to Have: Domain exposure to financial services / asset management / buy‑side valuation workflows. Direct experience with vendor Office add-ins — Capital IQ, Bloomberg, FactSet, MSCI, or similar. RPA familiarity (UiPath, Power Automate) as a fallback where UI-level automation is unavoidable. Observability (OpenTelemetry), IaC (Terraform), containerization, and Azure. Delivery in regulated / audited environments (access control, evidence, change control). #J-18808-Ljbffr

Vacancy posted 23 hours ago
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