Anaplan
AIAnalyticsEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“AI Analytics Engineer at Anaplan. Skills: AI Analytics, Backend Development, Cloud Infrastructure, Data Engineering, CI/CD. Develop backend services to collect and expose engineering and AI adoption metrics. Design and manage cloud infrastructure using Infrastructure-as-Code”
What You'll Achieve.
optimize business decision-making; outpace their competition and the market; empower data-driven decisions; support the effectiveness of our engineering teams; provide a unified view of engineering activity and AI tool usage; shape the engineering metrics and AI analytics strategy for a global engineering organization; build from the ground up; enable leadership visibility into engineering productivity and AI adoption
Industry & Context.
optimizing business decision-making; support the effectiveness of our engineering teams; provide a unified view of engineering activity and AI tool usage
What They're Looking For.
Must Have
3+ years of software engineering experience with Python, Experience designing and managing cloud infrastructure (preferably AWS) using Infrastructure-as-Code, Understanding of data engineering fundamentals such as columnar storage, partitioning, and analytics, Familiarity with secrets management and security best practices, Experience with CI/CD pipelines, containerization, and artifact management, Proficiency in designing and operating REST APIs, Comfortable with enterprise Git workflows and code review practices
Nice to Have
Experience with BI tools and analytics gateway configuration, Familiarity with AI/ML developer tooling metrics and enterprise AI adoption measurement, Experience integrating with identity and workforce platforms, Knowledge of container orchestration, Experience with document-oriented databases
What You'll Do.
Develop backend services to collect and expose engineering and AI adoption metrics
Design and manage cloud infrastructure using Infrastructure-as-Code
Build and maintain data pipelines that ingest
and store engineering metrics
Implement security and compliance best practices
Support CI/CD and delivery automation
Integrate with enterprise platforms
Document technical decisions and processes
How You'll Work.
Team & Collaboration
Engineering Enablement team; Cross-functional impact; collaborative, small-team environment
Communication Scope
Document technical decisions and processes to support team knowledge sharing and onboarding
Full Job Description
At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture. Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small. Supported by operating principles of being strategy-led, values-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! About the Role We are seeking an AI Analytics Engineer to join our Engineering Enablement team. You will help build and evolve the Engineering Metrics Service (EMS), a platform that collects, processes, and surfaces engineering productivity and AI adoption metrics across the organization. Your work will empower data-driven decisions and support the effectiveness of our engineering teams. What You'll Do Develop backend services to collect and expose engineering and AI adoption metrics from systems such as source control, AI tooling, and identity platforms Design and manage cloud infrastructure using Infrastructure-as-Code (e.g., Terraform) to support scalable, secure, and reliable data services Build and maintain data pipelines that ingest, transform, and store engineering metrics for analytics and business intelligence consumption Implement security and compliance best practices including secrets management, credential rotation, and
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