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Location: United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role The Marketing Analyst's primary responsibility is to help clients maximize value from their marketing data. You'll own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. You'll design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. This role also involves managing data transformations in dbt and working with complex, multi-source data architectures. You'll leverage AI tools (e.g. Codex, Claude) to accelerate your workflows. We are looking for someone who is reliable, responsible, quality-minded, keeps commitments, takes ownership of their work, and can confidently present results to clients. Responsibilities Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup. 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. Must Have Qualifications 3+ years of experience as Data Analyst with marketing data Expert-level proficiency in at least one BI platform (Looker, Power BI, or Tableau), with the ability to deliver projects across all. Proficiency in SQL Proficiency in data modelling (dbt preferred) Knowledge of Google Analytics (advanced level, for business understanding) Experience with Git English C1 level with excellent written and verbal communication ( client-facing role ) Strong analytical skills, proactive problem-solving, and high attention to detail Comfortable with ambiguity and able to drive clarity with clients and internal teams Hands-on experience with QA/UAT processes Proficiency with AI tools and ability to learn new ways of working is essential Nice to Have Knowledge of Google Analytics Data Streams . Familiarity with marketing platforms data (Google Ads, Facebook Ads, etc.). Understanding of Marketing Mix Modeling (MMM) concepts . Prior experience in marketing agency. What We Offer Remote-first environment. Competitive base salary. Stock options. Medical, and dental benefits. 401K plan. Unlimited PTO. 13 paid holidays. Professional development reimbursement.

Location: AL, United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role The Marketing Analyst's primary responsibility is to help clients maximize value from their marketing data. You'll own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. You'll design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. This role also involves managing data transformations in dbt and working with complex, multi-source data architectures. You'll leverage AI tools (e.g. Codex, Claude) to accelerate your workflows. We are looking for someone who is reliable, responsible, quality-minded, keeps commitments, takes ownership of their work, and can confidently present results to clients. Responsibilities Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup. 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. Must Have Qualifications 3+ years of experience as Data Analyst with marketing data Expert-level proficiency in at least one BI platform (Looker, Power BI, or Tableau), with the ability to deliver projects across all. Proficiency in SQL Proficiency in data modelling (dbt preferred) Knowledge of Google Analytics (advanced level, for business understanding) Experience with Git English C1 level with excellent written and verbal communication ( client-facing role ) Strong analytical skills, proactive problem-solving, and high attention to detail Comfortable with ambiguity and able to drive clarity with clients and internal teams Hands-on experience with QA/UAT processes Proficiency with AI tools and ability to learn new ways of working is essential Nice to Have Knowledge of Google Analytics Data Streams . Familiarity with marketing platforms data (Google Ads, Facebook Ads, etc.). Understanding of Marketing Mix Modeling (MMM) concepts . Prior experience in marketing agency. What We Offer Remote-first environment. Competitive base salary. Stock options. Medical, and dental benefits. 401K plan. Unlimited PTO. 13 paid holidays. Professional development reimbursement.

Location: GA, United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role The Marketing Analyst's primary responsibility is to help clients maximize value from their marketing data. You'll own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. You'll design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. This role also involves managing data transformations in dbt and working with complex, multi-source data architectures. You'll leverage AI tools (e.g. Codex, Claude) to accelerate your workflows. We are looking for someone who is reliable, responsible, quality-minded, keeps commitments, takes ownership of their work, and can confidently present results to clients. Responsibilities Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup. 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. Must Have Qualifications 3+ years of experience as Data Analyst with marketing data Expert-level proficiency in at least one BI platform (Looker, Power BI, or Tableau), with the ability to deliver projects across all. Proficiency in SQL Proficiency in data modelling (dbt preferred) Knowledge of Google Analytics (advanced level, for business understanding) Experience with Git English C1 level with excellent written and verbal communication ( client-facing role ) Strong analytical skills, proactive problem-solving, and high attention to detail Comfortable with ambiguity and able to drive clarity with clients and internal teams Hands-on experience with QA/UAT processes Proficiency with AI tools and ability to learn new ways of working is essential Nice to Have Knowledge of Google Analytics Data Streams . Familiarity with marketing platforms data (Google Ads, Facebook Ads, etc.). Understanding of Marketing Mix Modeling (MMM) concepts . Prior experience in marketing agency. What We Offer Remote-first environment. Competitive base salary. Stock options. Medical, and dental benefits. 401K plan. Unlimited PTO. 13 paid holidays. Professional development reimbursement.

Location: United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the Role The Marketing Analyst's primary responsibility is to help clients maximize value from their marketing data. You'll own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. You'll design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. This role also involves managing data transformations in dbt and working with complex, multi-source data architectures. You'll leverage AI tools (e.g. Codex, Claude) to accelerate your workflows. We are looking for someone who is reliable, responsible, quality-minded, keeps commitments, takes ownership of their work, and can confidently present results to clients. Responsibilities Build and maintain dashboards and reports in Looker, Power BI, and Tableau — depending on client setup. 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. Must Have Qualifications 3+ years of experience as Data Analyst with marketing data Expert-level proficiency in at least one BI platform (Looker, Power BI, or Tableau), with the ability to deliver projects across all. Proficiency in SQL Proficiency in data modelling (dbt preferred) Knowledge of Google Analytics (advanced level, for business understanding) Experience with Git English C1 level with excellent written and verbal communication ( client-facing role ) Strong analytical skills, proactive problem-solving, and high attention to detail Comfortable with ambiguity and able to drive clarity with clients and internal teams Hands-on experience with QA/UAT processes Proficiency with AI tools and ability to learn new ways of working is essential Nice to Have Knowledge of Google Analytics Data Streams . Familiarity with marketing platforms data (Google Ads, Facebook Ads, etc.). Understanding of Marketing Mix Modeling (MMM) concepts . Prior experience in marketing agency. What We Offer Remote-first environment. Competitive base salary. Stock options. Medical, and dental benefits. 401K plan. Unlimited PTO. 13 paid holidays. Professional development reimbursement.

Location: Georgia Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Armenia Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Brazil Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Argentina Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Serbia Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: Uruguay Improvado is an AI-powered marketing intelligence platform trusted by enterprise brands like ASUS, Activision, Docker, and H&R Block. We raised $34M Series A and are scaling fast — which means our infrastructure needs to be rock-solid. We're looking for a DevOps/SysOps engineer who takes ownership and keeps things running. What you'll do Manage and evolve our cloud infrastructure on AWS/Azure (Kubernetes) - ensure cluster reliability: capacity planning, autoscaling, incident response, and post-mortems Design and architect scalable, reliable infrastructure to support AI-driven analytics and data processing at scale Build and maintain Helm charts, Terraform, and multi-environment setups Own monitoring and alerting across the stack (Prometheus/Mimir, Grafana, CloudWatch) Administer and optimize storages: PostgreSQL, ClickHouse, Redis Support message brokers: RabbitMQ, AWS SQS, Temporal Drive infrastructure security: secrets management, IAM policies, vulnerability scanning, and encryption Own network design, configuration — VPCs, subnets, firewalls, load balancers, VPNs Monitor and optimize cloud costs — identify waste, right-size resources, and report on spend efficiency Participate in on-call rotation What we're looking for 5+ years in a DevOps/SRE role Solid hands-on experience with most of our stack (80%): AWS/Azure/GCP, Kubernetes (cluster design, capacity planning, and reliability at scale), Helm charts, CI/CD pipelines (GitHub CI), Terraform, PostgreSQL, ClickHouse, Redis, RabbitMQ, AWS SQS, Temporal, and monitoring/alerting stacks (Prometheus/Mimir, Grafana, CloudWatch) AI-assisted development in practice — actively uses Claude Code / agentic coding to ship, knows where AI-generated code needs validation Strong Linux fundamentals Bash and/or Python scripting Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Detail-oriented and pedantic, with sharp attention to detail in high-volume, high-stakes systems — accountable and genuinely invested in the quality of your work EST timezone availability Fluency in English Nice to have Golang or Python development background HashiStack: Vault, Packer ClickHouse administration Experience supporting data-intensive pipelines What we offer Remote-first environment 20 days PTO + US holidays Optional relocation support to Latin America Modern AI-native tech stack Stock options Professional development reimbursement A genuinely fun, transparent startup culture

Location: (Multiple States), United States About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Competitive compensation Medical and dental benefits 401K plan Unlimited PTO Paid holidays Professional development reimbursement

Location: (Multiple States), United States Improvado is an AI-powered marketing data platform built for mid-market and enterprise teams. We help companies automate complex marketing data workflows, unify data at scale, and surface insights through BI and AI. Brands like ASUS, Docker, Activision, and H&R Block rely on us to simplify analytics and improve marketing performance. We’re a fast-growing Series A startup backed by $34M in funding and driven by a team that moves fast, stays curious, and cares about high-quality execution. About the role The Account Executive uncovers business pains, articulates ROI, and builds the business case that helps prospects modernize how their marketing data works. You'll own a territory end to end — from first outreach to signed contract. Your buyers are marketing leaders, marketing ops and RevOps, and the data and analytics teams behind them. Some come to us; many you'll go and find yourself. It's a consultative, multi-stakeholder sale with a technical validation stage, so you'll work closely with our Sales Engineers along the way. Responsibilities Achieve a quarterly revenue quota across new business and expansion in your territory. Proactively generate new pipeline — you'll be expected to self-source at least 35% of your own opportunities, not just work inbound. Own the full sales cycle: discovery, demo, technical validation with a Sales Engineer, business case and ROI, executive presentation, negotiation and close. Build multi-threaded relationships — bring the technical evaluator, the budget owner, and your champion into the process early rather than running a deal through a single contact. Qualify with discipline. Confirm budget, decision path, and the real cost of doing nothing before pulling in technical resources — and walk away early from deals that aren't a fit. Become an expert at using Improvado's software, and at the marketing problems it solves. Coordinate the internal resources needed to win — Sales Engineering, Marketing, Customer Success — and keep every deal moving. Keep the CRM accurate and forecast honestly. Use AI in your day-to-day workflow — account research, call prep, follow-ups, first drafts. We'll expect you to work the way the company works. Leverage your creativity, intellect, and attitude in order to win new business. Qualifications 5+ years in a quota-carrying, full-cycle SaaS Account Executive role. 2+ years of experience in the MarTech/AdTech space. A track record of carrying and hitting a significant annual quota — you can walk through your numbers year by year with real examples. Experience selling to large enterprise organizations with multiple stakeholders and formal buying processes. Real outbound prospecting experience — you've built pipeline from scratch, not only worked inbound. Familiarity with ad platforms and the digital marketing funnel, and the metrics marketers are measured on. Comfortable in a technical sale — you can hold a credible conversation with a data team and then reframe it for a marketing leader. Experience in successfully initiating sales cycles with C-level executives. Ability to thrive in a constantly changing and evolving work environment. Emotional intelligence, natural curiosity, strong listening skills, and coachability. Superior communication and organizational skills. Comfortable with a modern sales stack (CRM, call recording and coaching tools, prospecting and enrichment tools, LinkedIn Sales Navigator) and with using AI tools in your own workflow. Experience working in a startup. Nice to have Experience selling to or working inside agencies. Formal training in a qualification methodology (MEDDIC / MEDDPICC or similar). What We Offer: Remote-first environment Competitive compensation Medical and dental benefits 401K plan Unlimited PTO Paid holidays Professional development reimbursement

Location: (Multiple States), United States About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Competitive compensation Medical and dental benefits 401K plan Unlimited PTO Paid holidays Professional development reimbursement

Location: Serbia We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Georgia We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Armenia We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Brazil We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period

Location: Argentina We're a fast-growing Series A startup ($34M raised, $10.3M ARR, 75% gross margin) building the unified marketing intelligence platform for enterprises like Spotify, Asus, and Colgate. Our Platform Team owns the core data pipeline infrastructure powering 500+ integrations — and we're now rebuilding how that work gets done, with AI at the center. We're looking for a Principal Engineer who can set the technical direction for AI-assisted engineering across the Platform Team — someone who doesn't just use AI tools, but defines how they're used responsibly at scale. About the Role You'll be the architectural voice on the Platform Team, shaping how we design, build, and evolve our core Python-based extraction and load infrastructure. More than that, you'll own the engineering practices shift: defining how agentic coding, AI-assisted development, and LLM tooling integrate into our delivery process without sacrificing reliability or maintainability. This is a hands-on role — you'll be writing code, reviewing architecture, and mentoring engineers, not just advising. Responsibilities Own platform architecture: design and evolve data extraction, load, and pipeline systems serving 500+ integrations at scale Identify architectural bottlenecks and drive performance/reliability improvements at scale (Kubernetes, distributed systems, ClickHouse/PostgreSQL) Lead modernization of legacy systems into scalable, AI-native infrastructure Design and implement agentic development frameworks for codebase maintenance and continuous improvement — owning the full loop from AI-assisted development to automated acceptance and rollout, with proper validation, testing, and architectural guardrails Make and document key technical decisions; set the bar for code quality, system reliability, and performance Mentor and level up engineers on AI-assisted development practices — help them ship faster without introducing hidden risk Collaborate cross-functionally with product and AI teams on agentic framework rollout and new integration capabilities Requirements 7+ years of backend engineering (hands-on programming), with at least 2 years in a principal/architect-level role owning production systems You've designed and scaled complex systems, not just maintained them Hands-on experience with AI-assisted development (Claude Code, agentic coding) — you ship with it, know its limits and where they break, and have built agentic frameworks for code maintenance and rollout Strong distributed systems background: Kubernetes, workflow orchestration (e.g. Temporal), message queues (e.g. RabbitMQ) Experience building secure systems that are hard to break, hard to breach, and resilient Experience with reliability practices at scale: observability, alerting, incident response Solid SQL and query optimization across PostgreSQL and ClickHouse Comfortable with ambiguity and high-velocity, fast-shifting priorities — we move like a startup, not a committee Ability to work within EST timezone Fluency in English Nice to Have Track record of defining engineering standards and driving adoption across a team Experience migrating legacy pipeline systems Background in data integration or ETL infrastructure What We Offer Remote-first environment Direct impact on platform architecture — your decisions matter Modern AI-native tech stack with real freedom to experiment 20 PTO days + US holidays Stock options Professional development reimbursement Optional relocation assistance to Latin America after trial period