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Salary
$108k – $195k per year (Estimated)
Location
Remote (Switzerland)
Seniority
Senior · 8+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is a Belgian recruitment platform built entirely around remote and flexible work, aggregating openings from thousands of employers that allow work from outside an office. Its matching engine ranks roles against a candidate's skills, seniority and stated preferences on location and flexibility, rather than leaving people to filter a keyword search, and it verifies how genuinely remote each posting is. The company also runs an AI screening layer that shortlists applicants for employers, and publishes research and guidance on distributed work practices alongside the job marketplace itself.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Developer for Analytics based in Switzerland.

This role offers the opportunity to design and build sophisticated analytics solutions that transform complex automotive and consumer datasets into valuable products and insights. You will connect data pipelines, analytical models, and user-facing applications within a modern cloud data environment. The position combines hands-on software engineering with technical leadership across complex, multi-team initiatives. You will shape engineering plans, lead architecture and code reviews, and help move data science and artificial intelligence prototypes into production. Collaboration with data scientists, AI engineers, and product leaders will be central to delivering scalable solutions. You will also mentor engineers, influence technical direction, and make pragmatic decisions that balance innovation, reliability, cost, and business value.

Accountabilities

    • Design technical solutions that integrate data pipelines, analytical models, and user-facing experiences into cohesive products.
    • Break complex analytics and Artificial Intelligence (AI) feature areas into clear engineering plans and identify technical risks early.
    • Lead code and technical design reviews, improving architecture, code quality, testing practices, and engineering standards.
    • Partner with data scientists, AI engineers, and product managers to shape experiments and transition successful prototypes into production-ready systems.
    • Mentor junior and developing engineers, sharing expertise in system design, debugging, technical decision-making, and stakeholder communication.
    • Own end-to-end analytical solution design, including data contracts, feature stores, model endpoints, and client integrations.
    • Design and evolve solutions on modern cloud data platforms such as Snowflake, Databricks, or Palantir Foundry.
    • Evaluate architecture and tooling decisions based on cost, risk, scalability, and business value.
    • Monitor developments in analytics and AI platforms and recommend new technologies when they provide meaningful value.
    • Select appropriate integration patterns and conduct Proofs of Concept (PoCs) to validate technical approaches and scalability.
    • Make informed build-versus-reuse decisions while balancing experimentation speed with reliability and long-term maintainability.
    • Communicate technical direction and trade-offs effectively with senior engineers, data scientists, AI engineering teams, product partners, and other stakeholders.
    • Requirements

      • Bachelor’s degree in Computer Science or a related field with approximately 8 years of relevant software development experience, or 6 years with a Master’s degree, or 3 years with a PhD; equivalent professional experience is also considered.
      • Proven experience owning delivery of complex, multi-team software or data engineering initiatives.
      • Strong production experience with Python, SQL, and Git, particularly in the development and operation of data pipelines.
      • Hands-on experience with a modern cloud data platform such as Snowflake, Databricks, Palantir Foundry, or an equivalent technology.
      • Strong understanding of scalable data architecture and integration patterns, including Extract, Transform, Load (ETL), Extract, Load, Transform (ELT), batch processing, and streaming.
      • Experience with JavaScript or TypeScript and React for developing customer-facing applications and interfaces.
      • Strategic mindset combined with the ability to remain hands-on and independently drive complex engineering initiatives.
      • Strong mentoring skills and a genuine interest in helping engineers develop their technical capabilities.
      • Clear communication skills, with the ability to explain technical concepts and trade-offs to both technical and non-technical stakeholders.
      • Strong decision-making skills in ambiguous environments, while maintaining awareness of broader business and product objectives.
      • Collaborative approach and ability to build effective working relationships with data science, AI engineering, and product teams.
      • Experience in automotive, consumer insights, or analytics-driven Software as a Service (SaaS) environments is desirable.
      • Experience mentoring engineers and leading technical design reviews is desirable.
      • Experience with PySpark or another distributed data processing framework is a plus.
      • Familiarity with Continuous Integration and Continuous Deployment (CI/CD), observability tools, and infrastructure-as-code is desirable.
      • Experience with cloud infrastructure across Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) is a plus.
      • Exposure to deploying AI or Machine Learning (ML) models into production analytics use cases is desirable.
      • Working knowledge of HTML, CSS, and data visualization libraries is beneficial.
      • Benefits

        • Full-time position.
        • Remote working arrangement within the United Kingdom.
        • Opportunity to work on sophisticated analytics and data products with global customer impact.
        • Exposure to modern cloud data platforms and AI-driven analytics applications.
        • Opportunity to influence architecture, engineering standards, and technical direction.
        • Significant ownership over complex feature areas and end-to-end solution design.
        • Opportunity to mentor engineers and contribute to the development of the wider engineering team.
        • Collaborative environment involving software engineering, data science, AI engineering, and product teams.
        • Opportunity to contribute to innovative, data-driven solutions within the automotive and consumer insights space.
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