Improvado

Backend Engineer

• Use AI tooling actively: Claude Code, prompt engineering, agentic coding to accelerate development, write tests, optimize complex problems, and ship faster
• Develop and maintain core data extraction and pipeline infrastructure serving 500+ integrations
• Own the architecture and execution of pipeline modernization initiatives
• Optimize product performance and reliability at scale: identify bottlenecks, manage resource constraints, and ensure data flows without disruption
• Drive technical decisions, and maintain high code quality

Python Engineer

QA Engineer

• Build AI-based testing frameworks and pipelines that automate the full QA workflow: design test strategies, develop automated tests, create and execute test plans, perform different types of testing across workflows, and analyze defects—all powered by LLM tools and modern AI frameworks
• Perform functional, regression, integration, and load testing across agent workflows
• Analyze defects and incidents, identify root causes, and help prevent regressions
• Collaborate closely with developers, product managers, and R&D on release validation
• Contribute to improving QA processes, test coverage, and automation practices

AI Engineer

• Own critical parts of our data extraction and pipeline infrastructure
• Work hands-on with AI to solve real infrastructure challenges
• Use AI tooling actively: Claude Code, prompt engineering, agentic coding to accelerate development
• Develop and maintain core data extraction and pipeline infrastructure serving 500+ integrations
• Own the architecture and execution of pipeline modernization initiatives
• Optimize product performance and reliability at scale: identify bottlenecks, manage resource constraints, and ensure data flows without disruption
• Drive technical decisions, and maintain high code quality

Data Analyst

• Build and maintain dashboards and reports in Looker, Power BI, and Tableau
• Write, optimize, and troubleshoot SQL queries for reporting, analysis, and investigations
• Manage and enhance data transformations with dbt where necessary
• Support clients directly — understand their requirements, translate them into data solutions, and deliver clear insights
• Conduct QA/UAT to ensure data accuracy, consistency, and trustworthiness
• Use Git for version control and collaboration
• Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly
• Leverage AI tools to be 10x more productive than the average analyst

Marketing Data Analyst

Marketing Analyst

• Help clients maximize value from their marketing data
• Own client delivery end-to-end for assigned accounts — from data modeling through final reporting
• Design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting
• Manage data transformations in dbt and work with complex, multi-source data architectures
• Leverage AI tools (e.g. Codex, Claude) to accelerate workflows
• Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly

• Help clients maximize value from their marketing data
• Own client delivery end-to-end for assigned accounts
• Design and maintain dashboards across BI platforms
• Ensure data quality and deliver clear, actionable reporting
• Manage data transformations in dbt
• Proactively identify opportunities, trends, or risks in marketing data
• Leverage AI tools to accelerate workflows

Middle Data Analyst, Marketing Experience

• Support clients directly — understand their requirements, translate them into data solutions, and deliver clear insights
• Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup
• Design and maintain data models that consolidate data from multiple marketing platforms and sources
• Map and document data flows across complex, multi-source schemas
• Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly
• Write, optimize, and troubleshoot SQL queries for reporting, analysis, and investigations
• Manage and enhance data transformations with dbt
• Conduct QA/UAT to ensure data accuracy, consistency, and trustworthiness
• Use Git for version control and collaboration

Senior Data Analyst, Marketing Experience

• Help clients maximize value from their marketing data
• Own client delivery end-to-end
• Design and maintain dashboards across BI platforms
• Ensure data quality and deliver clear reporting
• Manage data transformations in dbt
• Use AI tools to accelerate workflows

Senior Data Analyst – Marketing

• Support clients directly — understand their requirements, translate them into data solutions, and deliver clear insights.
• Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup.
• Design and maintain data models that consolidate data from multiple marketing platforms and sources.
• Map and document data flows across complex, multi-source schemas.
• Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly.
• Write, optimize, and troubleshoot SQL queries for reporting, analysis, and investigations.
• Manage and enhance data transformations with dbt.
• Conduct QA/UAT to ensure data accuracy, consistency, and trustworthiness.
• Use Git for version control and collaboration.

Senior Marketing Analyst

Content Marketing Manager

• Accelerate content-driven pipeline by building and operating systems that produce high-volume, high-relevance content.
• Own the full stack — from ideation infrastructure to production automation to SEO architecture to performance feedback loops.
• Build tools when none exist. Ship content when they do.
• Drive measurable organic growth through keyword strategy, content clustering, technical SEO fixes, and search-intent alignment.
• Track rankings and correlate SEO performance to pipeline.
• Demonstrate ability to hypothesize, test, and learn consistently.
• Maintain a quality bar where published content complies with internal styleguide and requires minimal revision from editorial leadership.
• Progressively automate content production to minimize human intervention.
• Build custom tooling where off-the-shelf solutions fall short.
• Keep content workflows documented, operational, and current. Proactively update systems when new technology or tooling emerges.

Content Strategy Lead

Infrastructure Engineer

• Design, build, and maintain AI-powered internal workflows to reduce manual work across departments — using tools like n8n, Make, or LLM-based agents as appropriate
• Implement and maintain MCP (Model Context Protocol) integrations to connect internal tooling and data sources
• Write and own automation scripts and integrations in Python and/or JavaScript; treat code readability and maintainability as a first-class concern
• Prototype agentic systems that solve real team pain points; iterate based on feedback — fast
• Own the administration and optimisation of our core SaaS stack: Google Workspace, Jira, Notion, and related platforms
• Manage identity and access controls, SSO, and RBAC across the organisation
• Maintain system reliability, handle incidents, and support day-to-day IT operations
• Apply security hygiene across the stack — access reviews, offboarding, audit logging, SOC 2-aligned controls
• Take ownership of workstreams end-to-end: scope, prioritise, deliver, and communicate progress without needing to be chased
• Operate at AI-era velocity — tasks are measured in hours, not weeks; use every tool available to get there
• Document systems, processes, and integrations clearly for async consumption by the wider team
• Engage proactively with stakeholders to understand tooling needs and translate them into structured delivery

AI & IT Infrastructure Engineer

Account Manager

• Work with clients to utilize marketing analytics and AI tools to analyze campaign performance, derive insights, and optimize strategies
• Prioritize customer success with a strong commitment to high-quality support and delivery
• Independently create detailed project and resource plans while collaborating closely with clients and internal Professional Services practice leads
• Lead strategic client meetings and consultations, providing guidance and expertise
• Manage client relationships end-to-end, maintaining accountability throughout the entire client lifecycle
• Partner closely with Sales, Engineering, Product, and Support teams to ensure alignment with company goals and seamless execution