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Associate Backend Software Engineer (Python)

Anaplan · Manchestermid

In short

  • ▸Desarrollas servicios backend en Python para soluciones predictivas y de forecasting en una plataforma empresarial.
  • ▸Trabajas con data scientists y ML engineers, integrando modelos en producción y gestionando pipelines de datos.
  • ▸Participas en on-call y colaboras en diseño, pruebas y mantenimiento de sistemas críticos con enfoque en calidad y escalabilidad.

Fluency in English is required for collaboration across global teams.

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What they ask for

  • ✓Experiencia profesional comprobada en desarrollo backend.
  • ✓Dominio de Python con código bien estructurado y testeado.
  • ✓Conocimientos en bases de datos relacionales y SQL (Postgres).
  • ✓Experiencia con contenedores y al menos una nube principal (AWS, GCP, Azure).
  • ✓Entendimiento básico de cómo funcionan los sistemas ML/AI en producción.
  • ✓Capacidad para actuar con iniciativa en entornos con cierta ambigüedad.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonPostgresAWSGCPAzureGitMLflowPrefectAirflowdbt

Who should you write to at Anaplan?

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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! You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the Syrup platform and Anaplan’s forecasting and predictive solutions. The team owns the production services behind forecasting, scoring, and data processing, along with the pipelines and infrastructure that bring ML and AI capabilities to enterprise customers. As a backend engineer, you will build and maintain core services across this stack, writing clean, well-tested Python while growing your craft alongside experienced engineers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with backend engineers, data scientists, and platform partners. Your Impact • Build and maintain backend services, APIs, and data processing components across the Predictive Intelligence stack. • Contribute to the forecasting, scoring, and data processing services that deliver predictive insights, with attention to performance, reliability, and code quality. • Write clean, well-tested, maintainable Python and follow established engineering best practices. • Work with data scientists and ML engineers to integrate models into production services and support the pipelines around them. • Participate in code reviews and design discussions, and incorporate feedback to grow as an engineer. • Take part in on-call rotations as you ramp, and help monitor, diagnose, and resolve issues across services and pipelines. • Collaborate across the team to deliver well-scoped features end to end. Your Qualifications • Proven commercial professional software engineering experience building backend services. • Solid proficiency in Python, with experience writing well-structured, tested production code. • Experience with relational databases and SQL (e.g., Postgres); familiarity with data warehousing technologies such as Snowflake is a plus. • Exposure to containerized services and at least one major cloud (AWS, GCP, or Azure). • Basic understanding of how ML and AI systems run in production and the data pipelines that support them. • Familiarity with version control (Git) and collaborative development practices. • Demonstrated ability to take ownership of well-scoped systems and deliver against requirements with some ambiguity. • Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Preferred Skills • Experience with data orchestration tools (e.g., Prefect, Airflow, dbt). • Familiarity with MLOps tooling such as MLflow, or ex

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