Marketing Engineer

Build the technology, intelligence, and automation behind UpCloud’s growth.

UpCloud is building the future of European cloud. We’re looking for aMarketing Engineerto help us build an equally ambitious Marketing function: one where trustworthy data informs decisions, predictive models uncover opportunities, and connected systems automate execution.

You’ll combine software engineering, data engineering, and data science to help every marketing function perform better. You’ll own our marketing technology stack, connect our platforms, build dashboards and analytical models, and turn complex data into clear recommendations.

This is a senior, hands-on role within Marketing, reporting to the CMO. You’ll work directly with marketing specialists to understand their challenges and build the tools, insights, and automation they need, collaborating closely with Data, Product, Engineering, Sales, and Finance.

Your mission: engineer a Marketing function that understands what happened, anticipates what comes next, and knows which actions to take.

What you’ll own

• Our marketing technology stack.Own the technical operation and evolution of the platforms Marketing depends on, including configuration, integrations, maintenance, reliability, and costs. Evaluate new tools and make informed build-versus-buy decisions across SaaS and self-hosted open-source solutions.

• Marketing data pipelines and models.Build and maintain pipelines that bring advertising, website, CRM, social media, product usage, and commercial data together in BigQuery. Develop reusable data models, consistent identifiers, and shared metric definitions. Make data quality, freshness, and traceability part of everyday operations.

• BI dashboards and self-service analytics.Design, build, and maintain dashboards in Google Data Studio / Looker Studio. Work directly with internal Marketing stakeholders to translate their questions into useful reporting, analytical datasets, and decision tools. Give each function a dependable view of its performance and the ability to investigate further.

• The progression from descriptive to predictive and prescriptive analytics.Build beyond dashboards and historical trends. Train and validate models using historical campaign, customer, product, and external data to forecast outcomes and identify emerging demand patterns. Develop prescriptive approaches that recommend next actions (budget allocation, audience priorities, lifecycle interventions, or the next experiment) using predictions, business constraints, and evidence from testing.

• New tools, channels, APIs, and MCP integrations.Continuously evaluate and connect the tools Marketing wants to experiment with. Build integrations through APIs, webhooks, connectors, and Model Context Protocol (MCP), where supported. This may include emerging advertising channels such as ChatGPT Ads, social media platforms, and new research, content, or experimentation tools. Ensure each experiment can feed useful data back into our shared analytics environment.

• Agentic workflows and process automation.Build agents and workflows that execute recurring marketing processes end to end, from gathering data and preparing campaigns to monitoring, optimization, and reporting. Enable autonomous execution within agreed goals, permissions, and budgets, with evaluation, monitoring, and clear exception handling.

The environment you’ll work with

Our environment combines SaaS and self-hosted platforms:

• Data and business intelligence:BigQuery and Google Data Studio / Looker Studio.

• Web, search, and product analytics:GA4, Google Tag Manager, Google Search Console, and self-hosted Matomo for control panel analytics.

• Consent management:iubenda.

• CRM and lifecycle automation:HubSpot.

• Website and SEO:WordPress and Semrush.

• Financial planning and reporting:Abacum, in collaboration with Finance.

• Advertising and social data:Sources including LinkedIn, X, Facebook, and other platforms used by Marketing.

• Emerging tools:New advertising channels, AI applications, experimentation platforms, and available APIs and MCP integrations.

You’ll help shape how these systems work together and what comes next. We value open-source technology and self-hosting where they offer meaningful advantages in control, flexibility, and total cost of ownership, balanced against delivery speed, reliability, and maintenance effort.

Useful additional experience

• Marketing mix modeling, causal inference, forecasting, optimization, or recommendation systems.

• Building and operating AI agents, LLM applications, or MCP integrations.

• Operating self-hosted open-source applications, including Linux, containers, and deployment automation.

• Working in B2B SaaS, cloud infrastructure, developer-focused products, or product-led growth.

You don’t need experience with every platform in our stack. We’re interested in your ability to build, analyze, learn, and deliver measurable improvements.

What success looks like

Marketing stakeholders have reliable dashboards, clear answers, and recommendations they can act on. Campaign and product data connect into a coherent view of customer behavior. Predictive models demonstrate useful performance against real outcomes, and prescriptive recommendations are tested for business impact.

Recurring work increasingly runs through dependable automation. Specialists can investigate performance and execute repeatable processes independently. Your impact shows up in faster decisions, reduced manual effort, stronger measurement, and better marketing results.