UPPeople

About the Product

We build a marketing data platform for the pharma industry. Our clients are pharmaceutical brands, and the campaigns reach verified healthcare professionals.

The platform enables marketing teams to run campaigns across channels such as Meta, LinkedIn, and programmatic advertising, and to measure campaign performance. The core product is a Laravel + Vue application running on GCP, backed by PostgreSQL and analytical data platforms including ClickHouse and BigQuery.

The team is small, fully remote across EU time zones, and releases continuously.

We are looking for a Lead Platform Engineer to lead the engineering team behind a large-scale web platform used by pharma marketing teams to run and measure their campaigns.

This is a hands-on technical leadership role. You will lead a small team of developers and a QA engineer while continuing to write code yourself. You will shape how features are built, translate product requirements into clear technical specifications, make architectural decisions, and take ownership from development through release and production.

You will work closely with the Product Lead, who owns the product vision and priorities, and report directly to the CTO. Together, you will shape not only the technology behind the platform, but also its user experience and evolution.

What we're looking for

General

• Product mindset: able to turn business goals into concrete user flows and product decisions, while challenging requirements that do not create real user value
• 2+ years of technical leadership: experience as a Tech Lead, Team Lead, or hands-on Engineering Manager, including task breakdown, code reviews, mentoring, and 1:1s
• 5+ years of full-stack engineering experience: building, shipping, and maintaining production web products
• Production ownership: comfortable owning releases, incidents, reliability, and data correctness
• Remote collaboration: comfortable working in a fully remote environment with overlap across EU time zones
• English B2+: confident in written communication, as most day-to-day communication is asynchronous

Technical

• UI/UX mindset: able to review existing user flows, identify friction, and implement meaningful improvements without depending on a designer for every change
• Strong Laravel: hands-on experience with Eloquent, queues, events, service providers, testing, and production Laravel applications
• Vue.js: experience with either Vue 2 or Vue 3. The existing SPA is based on Vue 2.7, Options API, Vuex, and Vue Router, so the ability to work effectively within an existing codebase is more important than framework preference
• PostgreSQL: beyond CRUD — indexing, query optimization, execution plans, and migrations against live production tables
• Strong SQL + analytical databases: practical experience with ClickHouse, BigQuery, Snowflake, or similar technologies
• Large-scale data: comfortable working with datasets containing hundreds of millions or billions of rows and understanding the performance implications
• Technical documentation: able to write and maintain FRDs, architecture decisions, API contracts, and data models
• GCP: experience designing and operating services using Cloud Run, Cloud SQL, GCS, or similar
• Docker & CI/CD: hands-on experience with Docker and CI pipelines, preferably GitHub Actions
• Automated testing: experience with unit, integration, and E2E testing and a mindset of improving test coverage over time
• Production debugging & observability: comfortable working with Sentry, application logs, infrastructure logs, monitoring, and incident investigation

Soft Skills

• Thinks in user flows, not just tickets — understands who the user is, what they are trying to achieve, and what should happen next
• Leads by doing: breaks down work, reviews code, mentors engineers, removes blockers, and makes difficult technical calls when necessary
• Strong written communication: can clearly document requirements, architecture decisions, and technical reasoning in English
• Analytical mindset: investigates root causes rather than treating symptoms
• Strong task and risk management: keeps work transparent, identifies dependencies, and raises risks early
• Responsible approach to healthcare data: understands the importance of access control, consent, privacy, and PII

AI & Engineering Automation

AI-assisted development is an integral part of the engineering workflow. We are looking for someone who actively uses AI coding agents rather than treating them as occasional productivity tools.

We expect you to:

• Use AI coding agents such as Claude Code, Cursor, Codex, or similar tools on a daily basis
• Be comfortable having AI draft a significant portion of production code while personally reviewing and validating the output
• Run multiple AI agents in parallel using isolated branches or worktrees
• Maintain project-specific AI context using tools such as CLAUDE.md, AGENTS.md, custom commands, and rules
• Build AI-powered automations for recurring engineering tasks such as reporting, migrations, release checks, or test generation
• Understand when AI-generated output is incorrect, incomplete, or unsafe — and know when to reject it
• Take full ownership of anything that reaches production, regardless of whether it was written by you or an AI agent

Nice to Have

• Experience with design systems or component libraries
• Experience with Figma or similar tools for designing and communicating user flows
• Experience defining product requirements directly with a Product Manager, founder, or business stakeholder
• Background in AdTech, MarTech, or marketing analytics
• Experience with healthcare or pharma products, particularly consent and PII handling
• Infrastructure as Code experience with Pulumi or Terraform
• Experience migrating Vue 2 to Vue 3
• TypeScript experience
• Apache Druid
• BigQuery or ClickHouse performance and cost optimization

Responsibilities

• Own the platform experience: make day-to-day UX and user-flow decisions and proactively identify improvements
• Partner with Product: contribute to what gets built, challenge assumptions, propose alternatives, and advocate for the user
• Lead a small engineering team: 2–4 developers plus QA, including task planning, code review, mentoring, and participation in hiring
• Stay hands-on: design and implement features yourself while distributing work across the team
• Own technical design: define data models, APIs, UI flows, testing strategy, and rollout plans
• Write and maintain FRDs and keep technical documentation up to date
• Work directly with the Product Lead on weekly priorities and delivery planning
• Work with large-scale campaign data across PostgreSQL, BigQuery, ClickHouse, and Druid
• Own releases and reliability: deployments, monitoring, alerting, incident response, and production support
• Improve observability and engineering quality across the platform
• Maintain and improve CI/CD and automated testing
• Work responsibly with healthcare-professional data, including access, consent, and PII requirements
• Report directly to the CTO and help define architecture and engineering standards

Tech Stack

Backend: PHP 8.3, Laravel 12, Redis
Frontend: Vue 2.7, Vuex, Vite
Databases: PostgreSQL, ClickHouse, BigQuery, Apache Druid
Cloud & Infrastructure: GCP, Docker, GitHub Actions
Monitoring: Sentry
Testing: PHPUnit, Cypress
AI: Claude Code and other AI coding agents

What We Offer

• Real ownership of a major product area, including its technical direction and user experience
• Fully remote work with flexible hours and overlap with EU time zones
• Direct access to the CTO and the opportunity to influence architecture and engineering standards
• Paid AI tooling, including Claude Code
• The opportunity to work with large-scale data, including datasets with up to 1.5 billion rows
• Complex real-world integrations with major advertising platforms
• A small, experienced engineering team with minimal bureaucracy and fast decision-making
• A role where you can influence what gets built, how it is built, and how the product evolves

Interview Process

1. Intro Call — 30 min: expectations and mutual fit.
2. Technical Interview — 90 min: architecture, data modelling, production failure modes, and AI-assisted development.
3. Product Lead Interview — 45 min: collaboration, product thinking, and ways of working.

We are looking for a Data Operations Manager to take ownership of the reliability, performance, and operational efficiency of our data platform.

We are also open to a strong Data Architect or Senior Data Engineer who has hands-on experience with data platform operations and is ready to take broader ownership of the data environment.

About the Role

You will be responsible for keeping our data platform reliable, scalable, observable, and cost-efficient. This is a hands-on role combining data engineering, platform operations, performance optimisation, data quality, and technical ownership.

You will work closely with Data Engineering, Analytics, BI, Security, and Finance teams to ensure that data is available, accurate, fresh, and delivered within agreed SLAs.

What You’ll Do

• Own and optimise our Snowflake data warehouse, including query performance, warehouse sizing, resource utilisation, and cost efficiency.
• Ensure the reliability and performance of dbt projects, covering data models, incremental processing, automated testing, documentation, and deployment.
• Oversee production ELT pipelines, ensuring data availability, freshness, reliability, and compliance with established SLAs.
• Build and improve monitoring, alerting, and incident management processes for the data platform.
• Lead root cause analysis and implement preventive measures to reduce recurring incidents.
• Establish and maintain data quality standards, automated validation, and observability practices across the platform.
• Manage data platform access controls, governance policies, and compliance requirements.
• Monitor Snowflake usage and credit consumption, identify optimisation opportunities, and contribute to platform budget planning.
• Develop operational runbooks, CI/CD workflows, and engineering best practices for data teams.
• Identify operational bottlenecks and continuously improve the reliability and efficiency of the data platform.
• Collaborate with Data Engineering, Analytics, BI, Security, and Finance teams on platform reliability, data quality, governance, and cost optimisation.

What We’re Looking For

• Extensive experience in Data Engineering, Analytics Engineering, DataOps, or Data Platform Operations.
• Strong hands-on experience with Snowflake administration, performance tuning, warehouse management, and SQL optimisation.
• Advanced experience with dbt Core or dbt Cloud, including incremental models, macros, testing, documentation, and deployment.
• Proven experience operating production ELT pipelines using Fivetran, Airbyte, Stitch, or similar tools.
• Strong understanding of DataOps practices, including CI/CD, Git/version control, automated testing, deployment pipelines, and production operations.
• Experience implementing data quality frameworks, monitoring, alerting, observability, and incident response.
• Good understanding of data governance, access management, security, and data platform reliability.
• Ability to troubleshoot complex data platform issues and drive them through to resolution.
• Strong ownership mindset and the ability to work independently across technical and operational areas.

Nice to Have

• Experience with data observability tools such as Monte Carlo, Elementary, or Datafold.
• Familiarity with workflow orchestration platforms such as Airflow, Dagster, or Prefect.
• Experience with cloud data platform cost optimisation, including Snowflake credit consumption and resource allocation.
• Knowledge of GDPR, SOC 2, or similar regulatory and compliance frameworks.
• Experience defining or improving data platform architecture and engineering standards.
• Previous experience acting as a Data Architect, Technical Lead, or Senior Data Engineer with ownership beyond individual pipelines or projects.

What Success Looks Like

In this role, success means having a data platform that is reliable, observable, predictable, and cost-efficient: pipelines run within SLAs, data quality issues are detected early, incidents are resolved systematically, Snowflake resources are used efficiently, and the engineering team has clear processes and tooling for operating the platform.

About the Product

We are a product company building a marketing data platform for the pharma industry. Our platform connects advertising channels, processes campaign data, and helps pharmaceutical brands understand the performance of their marketing campaigns.

We are looking for an Integration Team Lead to own the technical layer connecting our platform with advertising and data platforms. This is a hands-on technical leadership role: you will lead a team of 2–4 engineers, own integration architecture and roadmap, and continue contributing directly to the codebase.

The data your team processes ultimately powers the numbers our clients see in their dashboards, so reliability, data correctness, and observability are critical parts of the role.

You will report directly to the CTO and work closely with the Product team to prioritize the integration roadmap.

Fully remote · EU time zones

What You'll Do

• Own the architecture and evolution of platform integrations, including Meta Marketing API, LinkedIn Marketing API, CM360, DV360, with StackAdapt and TikTok integrations in progress.
• Lead a team of 2–4 engineers through task breakdown, code reviews, sprint planning, mentoring, and participation in hiring.
• Stay hands-on and contribute code alongside the team.
• Design and maintain integration pipelines end to end — from advertising APIs into BigQuery through Cloud Run Jobs, and onward into ClickHouse through Cloud Functions and Cloud Tasks.
• Work with BigQuery scheduled queries and versioned migrations, where a significant part of the transformation logic lives.
• Keep smaller integrations reliable as well, including PostgreSQL-to-Airtable synchronization.
• Define integration requirements and write FRDs before development starts.
• Maintain technical documentation, including integration contracts, data models, and operational runbooks.
• Ensure reliable synchronization through monitoring, alerting, error handling, retries, and backfill strategies.
• Build and improve CI/CD, secret management, and automated test coverage.
• Drive new integrations from API evaluation through production rollout.
• Prioritize the integration roadmap together with the Product team.
• Work directly with the CTO on architecture decisions and technical standards.

What We're Looking For

General

• 2+ years of experience leading engineers as a Tech Lead, Team Lead, or hands-on Engineering Manager, including code reviews, sprint planning, and mentoring.
• 5+ years of backend or data engineering experience with production systems you have supported yourself.
• Strong experience integrating third-party APIs at scale, including rate limits, OAuth, webhooks, asynchronous reports, and unreliable external services.
• Experience working in a fully remote environment with overlap across EU time zones.
• English B2+ — most of our communication is written and asynchronous.

Technical

• Strong Python 3.11 skills and experience writing production-grade code with error handling, structured logging, and automated tests.
• Practical experience with data pipeline patterns such as idempotency, backfills, incremental synchronization, and schema evolution.
• Hands-on experience with GCP, particularly Cloud Run services and jobs, Cloud Functions, Cloud Scheduler, Cloud Tasks, Cloud SQL, GCS, and Secret Manager.
• Strong SQL skills beyond basic CRUD, including experience implementing production logic directly in SQL.
• Experience with BigQuery, including scheduled queries and versioned migrations.
• Experience writing and maintaining technical documentation such as FRDs, integration contracts, data models, and runbooks.
• Experience setting up monitoring and alerting, working with logs, retries, and backfill mechanisms. Grafana experience is a plus.
• Hands-on experience with Docker and CI/CD and willingness to build and improve deployment pipelines.

Leadership & Soft Skills

• You lead by doing: you break down work, distribute tasks, review code, unblock engineers, and make decisions when necessary.
• You think in systems and understand the full chain from API ingestion to the end-user dashboard.
• When a number looks wrong, you investigate the source and data flow before changing the output.
• You keep the roadmap and engineering board aligned with reality and raise risks early.
• You are pragmatic, transparent, and comfortable communicating problems when something breaks.
• You can balance technical quality with business priorities and delivery timelines.

AI-First Engineering

AI-assisted development is already part of our engineering workflow. We expect you to be comfortable using AI coding agents as a daily engineering tool, not as an occasional experiment.

You should have experience with:

• Daily use of AI coding agents such as Claude Code, Cursor, Codex, or similar tools.
• Using AI agents to draft a significant part of the code you ship while reviewing and taking full ownership of the final result.
• Running multiple agents in parallel on isolated branches or worktrees and integrating their output yourself.
• Maintaining project-specific AI context through files such as CLAUDE.md, AGENTS.md, custom commands, or rules files.
• Automating recurring engineering routines with AI agents, such as reporting, migrations, release checks, or test generation.
• Critically evaluating AI-generated code and recognizing when an agent's output is incorrect or unsafe to ship.

AI is a tool, not a replacement for engineering judgment. Whatever reaches production, you own.

Nice to Have

• Hands-on experience with Meta Marketing API or LinkedIn Marketing API, including breakdowns, attribution windows, and asynchronous reports.
• Experience with workflow orchestrators such as Airflow, Prefect, or Temporal.
• Familiarity with the programmatic advertising and ad-server ecosystem: CM360, DV360, StackAdapt, TikTok.
• Understanding of advertising metrics such as impressions, clicks, conversions, ROAS, and attribution models.
• Experience in healthcare or pharma, particularly around consent and PII.
• Experience building AI agent harnesses, orchestrators, or MCP servers.
• Terminal-first engineering workflows using tmux or similar tools.
• Infrastructure-as-code experience. Our infrastructure uses Pulumi, with Terraform for the monitoring stack.

Tech Stack

Python 3.11 · GCP · Cloud Run · Cloud Functions · Cloud Scheduler · Cloud Tasks · Cloud SQL · GCS · Secret Manager · BigQuery · ClickHouse · PostgreSQL · Docker · Cloud Build · Pulumi · Terraform · Grafana · Slack · Claude Code

What We Offer

• Fully remote work with flexible hours and overlap with EU time zones for team collaboration.
• Direct access to the CTO — you will influence the architecture and technical standards of the integration layer rather than simply implementing predefined tickets.
• Paid AI tooling, including Claude Code.
• The opportunity to work with real advertising APIs and real production data volumes, including the edge cases that rarely appear in documentation.
• A small, low-bureaucracy engineering team where technical decisions can move quickly.
• Significant ownership over a critical part of the product and the opportunity to shape how the integration layer evolves.

About the Company

We are a product company developing a marketing data platform for the pharmaceutical industry. Our clients are pharmaceutical brands, and the campaigns running through the platform reach verified healthcare professionals.

The platform enables brand teams to run campaigns across channels such as Meta, LinkedIn, and programmatic advertising, and to measure campaign performance.

Our data infrastructure runs on GCP, with campaign statistics processed through BigQuery and ClickHouse. We are a small, fully remote team working across EU time zones and continuously shipping improvements to the product.

We are looking for a Data  Engineer to own the reliability and performance of our data platform. You’ll collaborate with engineering and business teams to ensure a reliable, scalable data environment.

Responsibilities

• Manage and optimise the Snowflake data warehouse, including query performance, warehouse sizing, resource utilisation, and cost efficiency.
• Maintain the reliability and performance of dbt projects, including data models, automated testing, documentation, and deployment processes.
• Oversee ELT pipelines, ensuring data availability, freshness, and compliance with established SLAs.
• Implement monitoring, alerting, and incident management processes, including root cause analysis and preventive measures.
• Establish data quality standards, automated validation, and observability practices across the data platform.
• Manage access controls, data governance policies, and compliance requirements.
• Monitor Snowflake consumption, implement cost optimisation strategies, and support platform budget planning.
• Develop operational runbooks, CI/CD workflows, and best practices for data engineering teams.
• Collaborate with Data Engineering, Analytics, BI, Security, and Finance teams to improve platform reliability and operational efficiency.

Requirements

• Extensive experience in Data Engineering, Analytics Engineering, DataOps, or Data Platform Operations.
• Strong hands-on experience with Snowflake administration, performance tuning, warehouse management, and SQL optimisation.
• Advanced proficiency in dbt Core or dbt Cloud, including incremental models, macros, testing, and deployment.
• Proven experience managing production ELT pipelines using Fivetran, Airbyte, Stitch, or similar solutions.
• Solid understanding of DataOps principles, CI/CD, version control, automated testing, and deployment pipelines.
• Experience implementing data quality frameworks, monitoring, alerting, and incident response processes.
• Understanding of data governance, access management, and data platform reliability.

Nice to Have

• Experience with data observability tools such as Monte Carlo, Elementary, or Datafold.
• Familiarity with workflow orchestration platforms such as Airflow, Dagster, or Prefect.
• Experience optimising cloud data platform costs, including Snowflake credit consumption and resource allocation.
• Knowledge of regulatory and compliance frameworks, including GDPR and SOC 2.

About the Company

We are a leading research and development company, recognized as one of the largest organizations in Ukraine specializing in fine organic synthesis and the development of advanced synthetic methodologies for organic compounds. Our scientific research contributes to cutting-edge innovations in the pharmaceutical and biotechnology industries, with projects that meet international standards.

Our culture is built around professional excellence, respect, teamwork, social responsibility, care for the scientific community, and proactivity.

We are looking for an experienced Lead Monitoring Engineer (SCOM) to architect, implement, and maintain a proactive enterprise monitoring platform based on Microsoft System Center Operations Manager (SCOM) 2022. Your mission will be to build a monitoring ecosystem capable of identifying and preventing service disruptions before they impact business operations or end users.

Responsibilities

• Design, deploy, configure, and maintain Microsoft SCOM 2022, including Management Servers, Gateways, Operational Database, and Data Warehouse.
• Build and support proactive monitoring for a hybrid Microsoft infrastructure, including:
  • Windows Server 2019+
  • Microsoft Exchange (On-Premises)
  • Microsoft 365 / Office 365 services
• Configure hardware monitoring for physical servers.
• Optimize monitoring quality by:
  • Establishing performance baselines
  • Reducing alert fatigue
  • Creating synthetic transactions and health checks
• Develop and maintain custom PowerShell scripts for automation, monitoring, and custom metric collection.
• Design monitoring standards, dashboards, alerts, and reporting to improve infrastructure visibility and reliability.
• Troubleshoot performance and infrastructure issues across enterprise environments.

Required Qualifications

• 3–5 years of enterprise Windows Server administration experience.
• 1–2 years of hands-on experience with enterprise monitoring solutions, preferably:
  • Microsoft SCOM (2012 R2 / 2016 / 2019 / 2022), or
  • Strong experience with Zabbix, PRTG, or Prometheus and a solid understanding of enterprise monitoring concepts.
• Deep knowledge of Windows internals, including:
  • WMI
  • Event Viewer
  • Performance Monitor (PerfMon)
  • Windows Registry
  • Performance troubleshooting (CPU, Memory, Disk I/O, Network)
• Good understanding of Microsoft Exchange architecture, including:
  • Database Availability Groups (DAG)
  • Mailbox databases
  • Transport queues
• Strong PowerShell scripting skills for automation and custom monitoring.
• Basic Microsoft SQL Server administration, including:
  • Indexes
  • Database file placement
  • High Availability concepts

Nice to Have

• Microsoft certifications such as:
  • MCSA / MCSE (Windows Server)
  • MCSE: Cloud Platform and Infrastructure
  • MCTS: System Center Configuration/Operations Manager
• Modern Microsoft certifications:
  • Microsoft Certified: Windows Server Hybrid Administrator Associate (AZ-800 / AZ-801)
  • Microsoft 365 Certified: Administrator Expert (MS-102)
• ITIL 4 Foundation certification or knowledge of Event Management and Incident Management processes.
• Basic XML knowledge for customization of SCOM Management Packs.

What We Offer

• A unique opportunity to design and build an enterprise monitoring platform from scratch, with significant architectural ownership.
• Work in a complex, enterprise-scale Microsoft infrastructure supporting mission-critical scientific operations.
• Official employment with full social benefits and a competitive, fully transparent salary.
• 24 calendar days of paid annual leave.
• Standard 40-hour work week.
• Fully remote work environment.
• Comprehensive medical insurance.
• Access to on-site dental and massage services (where applicable).
• Challenging and meaningful technical projects.
• Continuous learning, certification, and professional development opportunities.

We are looking for an Integration Team Lead. This is a technical management role: you lead a team of 2–4 engineers, own the integration architecture and roadmap, and stay hands-on in the code. Every number our clients see in a dashboard starts as an API call one of your pipelines made, so reliability and data correctness land on your desk first. You report directly to the CTO and prioritise the roadmap together with the product team. Fully remote, EU timezones.

Requirements
General
• 2+ years leading engineers as a tech lead, team lead or hands-on engineering manager: code review, sprint planning, mentoring
• 5+ years in backend or data engineering, with production systems you supported yourself
• Experience integrating third-party APIs at scale: rate limits, OAuth flows, webhooks, async reports
• Comfortable in a fully remote team with hours overlapping EU timezones
• English B2 or above. Most of our communication is written and async

Technical
• Strong Python 3.11: production-grade code with error handling, structured logging and tests
• Data pipeline patterns in practice: idempotency, backfill, incremental sync, schema evolution
• GCP at the service-design level: Cloud Run services and jobs, Cloud Functions, Cloud Scheduler, Cloud Tasks, Cloud SQL, GCS, Secret Manager
• SQL well beyond the basics, and comfort putting real logic into it. A large part of this pipeline lives in BigQuery scheduled queries and versioned BigQuery migrations rather than in Python
• Writing FRDs and keeping technical documentation current: integration contracts, data models, runbooks. We do not have this discipline today, and establishing it is a core part of the role rather than a bonus
• Monitoring and alerting you set up yourself: Grafana, logs, retry and backfill strategies. Today every alert path ends in Slack
• Docker, and CI/CD you will own. These services currently deploy from hand-run scripts with no pipeline and no tests in CI. Building that out is part of the job, not something you inherit finished

Soft
• You lead in practice: you split work for other people, review their code, unblock them, and say no when that is the right answer
• Systems thinking: you see the full chain from API ingestion to the end-user dashboard
• When a number looks wrong, you trace it back to the source before you change anything
• Task management: your roadmap and your team’s board reflect what is actually happening, and you raise risks while there is still time to act on them
• Pragmatic and transparent, including when something breaks: you say what happened and why, early

AI baseline
AI-assisted development is how we ship, not something we are piloting. Concretely, what we expect from day one:
• Daily use of AI coding agents (Claude Code, Cursor, Codex or similar): required, not “I tried it once”
• 50%+ of the code you ship is drafted by agents and reviewed by you line by line
• Able to run 2–4 agents in parallel on isolated branches or worktrees and merge the results yourself
• You maintain agent context for your projects: CLAUDE.md / AGENTS.md, custom commands, rules files. At least 1 such artifact you wrote yourself and keep current
• You automate at least 1 recurring routine per monthwith an agent: reports, migrations, release checks, test generation
• You can tell when the agent is wrong and throw the output away. Whatever ships, you are the engineer on the hook for it — we ask about this in the interview
Nice to have
• Hands-on experience with the Meta Marketing API or the LinkedIn Marketing API: breakdowns, attribution windows, async reports
• Experience with a workflow orchestrator (Airflow, Prefect, Temporal). We run on Cloud Scheduler and Cloud Tasks today, and we want a view on whether that should change
• The programmatic and ad-server ecosystem: CM360, DV360, StackAdapt, TikTok
• Advertising metrics and how they are computed: impressions, clicks, conversions, ROAS, attribution models
• Healthcare or pharma domain, especially consent and PII handling
• Building agent harnesses, orchestrators or MCP servers; terminal-first workflow (tmux or equivalent)
• Infrastructure as code. Our infrastructure is in Pulumi, with Terraform for the monitoring stack

Responsibilities
• Own the architecture and evolution of all platform integrations: Meta Marketing API, LinkedIn Marketing API, CM360 and DV360, with StackAdapt and TikTok in flight
• Lead a team of 2–4 engineers: code review, sprint planning, mentoring, input into hiring
• Stay hands-on: you write code yourself as well as distributing it
• Design and maintain the pipelines end to end: ad-platform APIs into BigQuery through Cloud Run Jobs, onward into ClickHouse through Cloud Functions and Cloud Tasks, with a large share of the transformation in BigQuery scheduled queries
• Keep the smaller integrations healthy too, such as the five-minute PostgreSQL to Airtable sync
• Write the FRD before an integration starts and keep the technical documentation current after it ships
• Keep sync reliable: monitoring, alerting, error handling, retry and backfill strategies
• Build out CI/CD, secret handling and test coverage for these services
• Drive new integration projects from API evaluation to production rollout
• Prioritise the integration roadmap together with the product team
• Report to the CTO and agree architecture and technical standards with them

Tech stack
Python 3.11 · GCP (Cloud Run services and jobs, Cloud Functions, Cloud Scheduler, Cloud Tasks, Cloud SQL, GCS, Secret Manager) · BigQuery, ClickHouse, PostgreSQL · Docker, Cloud Build, Pulumi, Terraform · Grafana, Slack · Claude Code

What we offer
• Fully remote with flexible hours, overlapping EU timezones for syncs
• A direct line to the CTO: you shape the architecture and technical standards of the integration layer, and technical direction is agreed with the CTO rather than handed to you as tickets
• Paid AI tooling, including Claude Code
• Ad-platform APIs that fail in ways no documentation describes, at real data volumes
• A small team with no bureaucracy, where decisions happen the same day

 

About the role
We're looking for a hands-on data platform expert to own the reliability, performance, and cost-efficiency of our modern data stack, built on Snowflake, dbt, and managed ELT. You'll be the go-to person for how data flows, how fast it runs, and how much it costs. You'll also shape the operational standards our data teams build on.

If you're a strong Data Architect or Senior Data Engineer who enjoys making platforms run smoothly at scale, we'd love to talk.

What you'll do

• Own Snowflake performance and cost. Tune queries, right-size warehouses, track credit consumption, and drive cost optimisation and budget planning.
• Keep dbt production-grade. Maintain models, automated tests, documentation, and deployment processes.
• Run reliable ELT. Oversee pipelines end to end so data stays available, fresh, and within SLA.
• Build observability. Set up monitoring, alerting, and incident management, and lead root cause analysis and prevention.
• Set the data quality bar. Define standards, automate validation, and embed observability across the platform.
• Govern access and compliance. Manage access controls, governance policies, and regulatory requirements.
• Scale good practices. Create runbooks, CI/CD workflows, and engineering standards for data teams.
• Partner across functions. Work with Data Engineering, Analytics, BI, Security, and Finance to raise platform reliability and efficiency.

What you bring

• Extensive experience in Data Engineering, Analytics Engineering, DataOps, or Data Platform Operations
• Strong hands-on Snowflake expertise: administration, performance tuning, warehouse management, and SQL optimisation
• Advanced dbt (Core or Cloud) skills, including incremental models, macros, testing, and deployment
• Proven experience running production ELT with Fivetran, Airbyte, Stitch, or similar tools
• Solid grasp of DataOps practices: CI/CD, version control, automated testing, and deployment pipelines
• Track record of implementing data quality frameworks, monitoring, alerting, and incident response
• Understanding of data governance, access management, and platform reliability

Nice to have

• Data observability tools such as Monte Carlo, Elementary, or Datafold
• Orchestration with Airflow, Dagster, or Prefect
• Hands-on experience cutting cloud data platform costs, especially Snowflake credits
• Familiarity with GDPR and SOC 2

We are looking for a Lead Platform Engineer to lead the team behind a web platform used by pharma marketing teams to run and measure their campaigns.

This is a hands-on technical leadership role: you will lead a small team of developers and a QA engineer while continuing to write code yourself. You will work closely with the CTO and Product Lead, taking features from technical design and documentation through development, release, and production.

What you’ll do

• Lead a team of 2–4 developers + QA: break down tasks, review code, mentor engineers, and contribute to hiring
• Stay hands-on and write production code yourself
• Design how features should be built: data model, API, UI, testing, and rollout
• Write and maintain FRDs, architecture decisions, API contracts, and data models
• Work directly with the Product Lead on priorities
• Work with large-scale campaign data across PostgreSQL, BigQuery, ClickHouse and Apache Druid
• Own releases, production reliability, monitoring, incident response, and debugging
• Improve automated testing, observability, and development processes
• Work with healthcare-professional data, including access, consent and PII requirements
• Report directly to the CTO and participate in architecture and technical decisions

Requirements

• 2+ years as a Tech Lead, Team Lead or hands-on Engineering Manager
• 5+ years of experience building and shipping web products as a full-stack engineer
• Strong hands-on experience with PHP / Laravel
  • Laravel 12, PHP 8.3
  • Eloquent, queues, events, service providers, testing
• Experience with Vue.js and working with an existing Vue codebase
  • Vue 2/3, Vuex, Vue Router
• Strong PostgreSQL knowledge: indexing, query plans, migrations on live tables
• Strong SQL skills and experience with an analytical database such as ClickHouse, BigQuery, Snowflake or similar
• Experience working with large datasets
• GCP experience: Cloud Run, Cloud SQL, GCS
• Docker and CI/CD experience, preferably GitHub Actions
• Experience with automated testing and production debugging
• Experience writing technical documentation and feature requirements
• English B2+
• Comfortable working remotely with overlap with EU time zones

AI-assisted development

AI-assisted development is an important part of the workflow. We expect you to:

• Use AI coding agents such as Claude Code, Cursor, Codex or similar on a daily basis
• Be comfortable reviewing and validating AI-generated code
• Work with multiple coding agents in parallel using isolated branches/worktrees
• Maintain project context and rules for coding agents, e.g. CLAUDE.md / AGENTS.md
• Use AI agents to automate recurring engineering tasks such as test generation, migrations, reports or release checks
• Take full responsibility for the code that reaches production

Nice to have

• Ad-tech or marketing analytics experience
• Healthcare or pharma domain experience
• Pulumi or Terraform
• Experience migrating Vue 2 to Vue 3
• TypeScript
• Apache Druid
• BigQuery / ClickHouse performance and cost optimization

What we offer

• Fully remote work with flexible hours and EU timezone overlap
• Direct collaboration with the CTO on architecture and technical standards
• Paid AI tooling, including Claude Code
• Work with large-scale datasets, including tables with up to 1.5 billion rows
• Small, technically focused team with minimal bureaucracy
• Opportunity to influence architecture and engineering practices rather than simply implement predefined tickets
   

About the product

The product is a marketing data platform for the pharma industry. It helps pharmaceutical brands run campaigns across Meta, LinkedIn and programmatic channels and measure their performance.

The core product is a Laravel + Vue application running on GCP, with PostgreSQL, ClickHouse, BigQuery and Apache Druid behind it.