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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # FinOps Platform Engineering, Sr. Manager - **Company:** Medidata Solutions, Inc. - **Location:** Woodbridge Township, NJ, United States - **Experience:** Expert - **Salary:** $114,750.0 - $153,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Build Automation, Clinical Data Repository, Continuous Integration, Information Engineering, Cursor (Graphical User Interface Elements), Decision Support Systems, DevOps, Python (Programming Language), Standard Sql, Software Engineering, Systems Integration, Tableau (Software), Data Ingestion, Large Language Models, Snowflake, Terraform, Software Version Control, Data Pipelines - **Published:** September 12, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88314160/1 ## About the Role * 7+ years of experience in Software Engineering, Data Engineering, Platform Engineering, or DevOps, with a Bachelor's degree; hands-on experience building FinOps or cloud cost management capabilities, products, or services is a strong plus. * Demonstrated fluency building with AI coding tools (Claude Code, Cursor, or comparable) as an integral part of your production engineering workflow. * Hands-on engineering skills: proficiency in Python or a comparable language, strong SQL, and experience designing APIs and data pipelines. * Hands-on expertise with AWS and Snowflake, including integrating with cloud provider billing and usage data (e.g., AWS Cost & Usage Reports, Snowflake usage views) and BI/analytics platforms (e.g., ThoughtSpot, Tableau). * Experience with infrastructure-as-code and automation (e.g., Terraform, CI/CD) sufficient to enforce tagging and policy at deploy time. * Ability to design and ship self-service tooling for internal stakeholders - a product mindset applied to an internal function. * Experience building alerting or anomaly-detection systems, or automating financial/operational calculations, is a plus. * Experience metering or governing AI/LLM usage and spend (token-level cost attribution, LLM gateways, or usage telemetry) is a plus. * Ability to work independently to stand up new integrations with minimal direction, in service of a standalone, self-sufficient FinOps function. * Strong communication skills, with the ability to partner closely with the FinOps Architect (technical framework design) and Program Manager (delivery cadence). * Exposure to regulated or compliance-driven environments is a plus. ## Description FinOps operates like a product team: the business - Engineering, Product, Finance, Procurement, and Operations - is our customer, and cost/usage insight is the product. The FinOps Platform Engineering, Sr. Manager is the technical builder who makes that possible: this role owns the tooling, integrations, and automation that let FinOps operate as an autonomous, standalone unit rather than a group of people manually pulling numbers on request. This is a hands-on engineering role at the Sr. Manager level. You will design, code, and ship the FinOps platform yourself - the title reflects seniority and scope of ownership, not a coordination or people-management function. Responsibilities: * Design, build, and maintain the tooling and integrations that connect cost and usage data sources - AWS, Snowflake, and HDC (our clinical data cloud) - into a unified FinOps platform. * Build automated tagging enforcement and validation pipelines against the framework defined by the FinOps Architect, so compliance is built in at deploy time, not checked after the fact. * Build self-service tools and APIs that let Engineering, Product, and Finance pull their own cost and usage insights on demand - treating internal stakeholders as customers of a product, not requesters in a queue. * Own the data pipelines feeding executive and team-level dashboards (ThoughtSpot, Unified Portal), including reconciliation logic that ties attributed and unattributed spend back to the invoice - automating what would otherwise require manual analysis. * Automate cost allocation, showback/chargeback calculations, and unit-economics computations (e.g., cost per trial, cost per environment). * Instrument and meter AI/LLM usage and spend across providers - token-level telemetry, attribution to teams and workloads, and integration with gateway and measurement tooling - so AI cost is as visible and governable as cloud cost. * Build integrations with vendor and procurement systems to automate renewal tracking, contract data ingestion, and scorecard generation. * Build anomaly detection and automated alerting on cost and usage data, closing the gap between a monthly report and a real-time signal. * Build automation to audit and optimize Savings Plan / Reserved Instance coverage, rather than tracking it manually. * Partner with Engineering to instrument systems for cost and usage telemetry at the source, including detection of cost regressions introduced by code and configuration changes. * Own the technical roadmap for FinOps tooling, including build-vs-buy decisions on platform components. * Apply standard engineering rigor - version control, testing, CI/CD - to the FinOps tooling stack. * Promote a culture of accountability, continuous improvement, and data-driven decision making. ## Related Videos - [Move Fast, Break Budgets: FinOps in the Age of DevOps and AI](https://www.wearedevelopers.com/videos/2016-move-fast-break-budgets-finops-in-the-age-of-devops-and-ai) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [DevOps Engineer Salary [2023]](https://www.wearedevelopers.com/magazine/203-devops-engineer-salary-2023) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025)