Senior Software Engineer, Python, Cloud, Data

• Join a client's data science and product team and collaborate with business stakeholders
• Turn internal apps prototyped in Lovable into secure, production-grade services on Cloud Run
• Build backends and middle layers with authentication, audit trails, and secure document storage
• Build and orchestrate data feeds from Salesforce and third-party data providers to the canonical data layer, dashboards, and planning tools such as Pigment and Anaplan
• Automate recurring reporting and analysis, including scheduled data centralisation and quarterly metrics with manual overlays
• Own the security of everything shipped
• Provide technical review of AI Skills used by business teams
• Document work through READMEs, runbooks, and architecture notes
• Explain trade-offs to non-technical stakeholders and flag technical risks and sequencing concerns
• Decline scope belonging to other teams

• Around 4–7 years of hands-on commercial software engineering experience
• Strong production Python skills across services and data pipelines, including testing and CI/CD
• In-depth cloud experience with compute, managed databases, serverless, and IAM; GCP preferred, AWS or Azure also counts
• Full-stack range, strongest on APIs and the middle layer, with ability to adjust a React/TypeScript front end without a designer
• Data engineering experience with API, database, and file-extract ingestion; orchestration, preferably Airflow; and SQL, ideally NoSQL, schema design
• Proven experience taking prototypes or AI-generated code to production and owning a service end to end, including deployment, monitoring, and documentation
• Hands-on experience securing services, including authentication, least-privilege IAM, secrets handling, input validation, audit logging, dependency hygiene, and secure document storage and retention
• Autonomy and commercial awareness when handling unclear briefs, unfamiliar systems, and undocumented tables
• Experience building integrations with Salesforce or planning platforms such as Pigment and Anaplan
• Knowledge of canonical or dimensional data modelling
• Exposure to LLM workflows and prompt evaluation
• Experience with Lovable or Supabase

• Flexible and remote cooperation options
• International projects with leading global clients
• Travels related to international projects
• Non-corporate atmosphere
• Access to language classes
• Access to knowledge-sharing initiatives
• Access to private healthcare and life insurance
• Access to multisport card