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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

Improvado14 ч назад

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

Improvado14 ч назад

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

Improvado14 ч назад

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

Improvado14 ч назад

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

Improvado14 ч назад

Location: Serbia AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Argentina AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Georgia AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Brazil AI Product Builder Improvado is an AI-powered, unified platform designed for marketing teams in medium to large-scale enterprises and agencies, who are looking to automate complex marketing intelligence and reporting to make decisions with ease. Improvado gathers, organizes, and untangles marketing data to deliver instant insights through BI and AI, helping to eliminate complexity, delivering laser-focused insights to optimize budgets, enhance campaign efficiency and marketing ROI. About the role As an AI Product Builder you own one product area end to end. Which area depends on where we need you most, and the work is the same in all of them. Our products turn marketing data into decisions, and each of them has the same failure mode: it tells the customer something and stops there. Your job is to find where your area stops short of causing a decision, build the part that closes that gap, and show that somebody acted. You will build hands-on with AI, shape the roadmap, work directly with engineering teams and with customers, and decide what a good recommendation looks like for a different persona on the same data - a media buyer, an analyst and a CMO do not want the same thing. Responsibilities Own the product area end to end, from idea to delivery, and define how the roadmap evolves Close the gap between what the product reports and what the customer does about it: decide what gets recommended and to whom, and build the loop that makes those recommendations better over time Work hands-on with AI, from mockups and prototypes through to production code for smaller features, alongside an engineering team of three to ten people Run customer discovery yourself and turn it into roadmap decisions Define and measure the metrics that prove the product caused someone to act Build and maintain automated workflows using AI tools, scripting and the modern data stack Collaborate with Product, BI and CSM teams on architecture decisions and customer data requirements Qualifications Product ownership experience - able to take a problem end to end with minimal hand-holding, and point at things you built that are still in use Demonstrated use of AI tools in daily work: Claude Code, agentic coding, prompt engineering, with a clear view of what you deliberately do not delegate Experience building an AI agent and making it reliable in production Marketing or revenue data domain experience, and you have computed those metrics yourself rather than receiving them from an analyst Comfortable working with engineers as a peer rather than across a handoff Strong SQL ; Python for data processing and automation Fluent English - there are customer calls and escalations in this role Availability to overlap US Pacific business hours (or at least East) Nice to have Hands-on ETL/ELT pipeline experience (BigQuery, Snowflake, Redshift, or ClickHouse) Experience working directly with clients on technical requirements BI tools (e.g. Superset) for operational reporting Process A screening call, a 45-minute call with the VP of Product, a take-home designed for 90 minutes to two hours, and a review of it with our product managers. What We Offer Remote-first environment Optional relocation assistance to Latin America after your trial period Strong product/market fit: marketing data product for US-based enterprises Modern AI tech stack and freedom to experiment High-velocity team where you will constantly learn and scale your skills High autonomy and ownership - we care about outcomes, not hours AI-first, collaborative, no-bureaucracy culture with a technically strong, international team 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Argentina About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Serbia About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Mexico About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Brazil About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Ecuador About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Uruguay About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад

Location: Montenegro About Improvado 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 Genentech, T-Mobile, 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 Improvado is a marketing data platform for enterprise brands and agencies. You will own how our revenue runs and how it is measured. That covers Salesforce and the GTM tools, the path from signed contract to paid invoice, the revenue data model, and the reports leadership decides from. You work closely with the analytics team: you don’t have to build the data models yourself, but you must read them, spot what is wrong and say what to change. You work through AI agents daily, doing the work of a bigger team. What you will do Salesforce and GTM stack Own Salesforce configuration, release process and user access, plus the integrations around it (Gong, Clay, Lemlist, enrichment, e-signature, lead routing). Keep CRM data clean with guardrails that block mistakes. Manage licences and vendor renewals. Maintain the Salesforce manual and RevOps SOPs, and train new hires. Contract to cash Own ARR and bookings logic (new, upsell, downsell, churn, renewals) and keep agreement, opportunity, and invoice consistent. Run the closed-deals and billing check with Finance. Fix errors at the source and add a control so they don’t repeat. Audit invoices, track and chase unpaid ones, and prepare quarterly commission and quota reports. Revenue analytics and data model Own the quarterly sales analytics pack, the CRO report, the forecast and pipeline coverage (including CS renewal inputs). Track funnel conversion, explain why deals move, stall or slip, and keep attribution correct with Marketing. Query ClickHouse daily, trace any number to its source, and write specs for model changes. Give each metric one documented definition and add data quality checks. Build leadership dashboards, retire unused ones, and end every analysis with a recommendation, a number and an owner. AI and automation Use coding agents (Claude Code, Codex) for queries, scripts and Salesforce automation, and always verify their output. Automate manual work (invoice and payment checks, CRM hygiene, deal-risk alerts, call analysis) and measure hours saved and errors avoided. Ownership Be the single RevOps contact for Sales, CS, Marketing, Finance and Product. Turn each request into a task with an owner, date and success metric. Requirements 4-6+ years in RevOps, Sales Ops or GTM systems in B2B SaaS, with hands-on admin of a live Salesforce org. Strong SQL and comfort in a modeled warehouse (layers, lineage, one definition per metric). dbt is a plus. Deep knowledge of the B2B SaaS revenue cycle: funnel, pipeline, forecast, ARR, churn, renewals. Experience running the money side: contracts, invoicing, collections, kept in sync with the CRM. Proof you build with AI agents: something you shipped that others use. Fluent English and clear written updates without being asked. Nice to have Salesforce Administrator or Advanced Administrator certification. ClickHouse or another columnar warehouse, and any BI tool. Salesforce development (Apex, triggers, API). Gong, Clay, Lemlist, or workflow automation tools. Billing, CPQ, or accounting systems. HubSpot to Salesforce migration. Attribution or CS health score data. Martech or analytics company background. What We Offer Remote-first environment Strong product/market fit: marketing data product for US-based enterprises 20 working days of PTO per year US holidays and additional days off Professional development reimbursement

Improvado14 ч назад