InsulaLabs

We are looking for a Senior Data Analyst. 

This is not a standard analyst role. We are building a dynamic identity resolution system where AI is deeply integrated — both as a productivity multiplier and as a core component of our data processing logic for identity resolution and LLM-based scoring.

We run enrichment against 70+ TB of data, apply AI and LLM-based scoring on top, and process around 20 million enrichment operations per day across hundreds of thousands of records.

The analytical challenges ahead are substantial: how to measure the quality of AI-driven scoring, how to validate that a change makes the system better, how to know where our money and time deliver the most value, and how to turn the questions our internal teams bring in into fast data-backed answers. You will own this side of the business, working daily alongside engineers and the product lead to turn these challenges into decisions that ship.

The main part of the role is not building dashboards — it is the data work that makes a meaningful dashboard possible in the first place. Concretely, you will be:

• Looking at data from multiple vendors side by side and deciding what to trust.
• Reconciling entities across sources that have different shapes and quality.
• Proposing and validating the logic that matches and scores them.
• Defining metrics and ground truth for questions nobody has asked before.
• Tracing why numbers don't line up across partial and sometimes contradictory sources.

Dashboards and visualizations are part of how findings get communicated, but they come at the end — the surface of the work, not its core. Most of your time is spent on what sits underneath: methodology, judgment calls on data quality, and shaping how the domain understands its own numbers.

Responsibilities

• Measurement & Evaluation Foundations: Define how we measure what matters — data quality, the accuracy of our AI scoring, how many records actually get matched to usable signals, cost per outcome. Build the feedback loops that tell us whether a change makes the system better or worse.

• Scoring Intelligence (co-owned with engineers): Partner with the engineering team on the LLM-based scoring system. You will build the evaluation framework for AI scoring, run experiments comparing prompts, models, and approaches against a baseline, and make data-backed calls on where we invest next. Our AI scoring system is actively evolving — you will shape how we measure and improve it.

• Client-related Analysis: Own the analytical side of the work that internal sales and media-buying teams bring in from pharma clients — how reachable a target audience is, how good the data looks, why a campaign performed the way it did. You turn their questions into data-backed answers they can use. Identity is a product core; the analyst works with internal teams, not with clients directly.

• Cost and Value Analysis: Turn cost and value into product decisions. Which data sources and enrichment scenarios pay off, where we overspend, what to cache, what to cut. We operate a mix of free owned data and paid external providers — the decisions have real dollar impact.

• Active AI Usage: Use Claude Code and modern AI engineering tools to multiply your own output. Automate the repetitive parts of analysis so you can focus on the decisions. We provide Claude Code licenses and expect active daily use.

• Data Quality Response: When pipeline output drifts, a provider degrades, or upstream data shifts, you notice first, diagnose the root cause, and drive the fix. You treat data quality as a product, not a ticket queue.

Requirements

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team (not consultancy, not BI-only roles).
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. You can read and write complex queries on tens of terabytes without someone pre-modelling the data for you.
• Python for analysis at a working level — pandas, Jupyter, or modern equivalents. Comfortable putting together a small script or helper when an existing tool doesn't cover your case.
• Built measurement or evaluation frameworks from scratch for systems that had no baseline. You are comfortable defining what and how to measure, not consuming someone else's KPI.
• Comfort with probabilistic systems. You understand that noise is inherent and 100% accuracy is not the goal — scoring, matching, ranking.
• AI-native workflow. You already use Claude Code, ChatGPT, Copilot, or similar AI tools daily and integrate them into your analytical process.
• English: B2+ (Upper-Intermediate) or higher.

Strong plus (one or more)

• LLM evaluation experience — A/B testing AI-powered features, output scoring, prompt iteration with measurable outcomes.
• Identity resolution / identity graph experience — adtech, martech, or customer data platform context (LiveIntent, LiveRamp, Epsilon, Experian Marketing, Acxiom, Merkle, or similar).
• Healthcare or pharma data — working with NPI, HCP-level data, healthcare taxonomies, pharma targeting.

Nice to have

• Experience running controlled experiments on data pipelines.
• Prompt engineering or structured LLM prompt design.
• Prior work in AI-first product companies.

Culture & Mindset

• Self-improvement: You are a fast learner. You don't fear AI replacing you; you master it to replace your manual tasks.
• Ownership: You treat the Identity domain as your own business. If scoring quality drifts or a provider degrades, you notice it and drive the fix without being asked.
• Internal Locus of Control: You take responsibility for outcomes. If external data shifts or an API changes, you build around it instead of blaming the provider.
• Get It Done: You prioritize shipping answers. You know when to send a rough estimate and when to build a proper framework.
• Openness: You share findings and admit mistakes openly — both wins and failures travel across the team. If you spot a better way to do something, you volunteer it without being asked.

What We Offer

• Fully remote with flexible hours, with working overlap in CET ±2 hours for syncs.
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech — both for daily work and as part of product logic.
• High-Impact Role: You will directly shape how we identify, score, and reach healthcare professionals — the core business of our domain.
• Small team, direct impact: You will work directly with Product and Engineering leads — no layers between you and the people making decisions.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

Hey! 👋

We’re looking for an experienced Program Manager to join our dynamic team and lead large-scale delivery operations across multiple projects!
 

🟢 Full Remote
🕘 Working hours: 9:00–18:00
 

Requirements:

✔️ 7+ years of experience in IT

✔️ 3+ years of experience in Program / Delivery Management

✔️ Experience in supervising and mentoring Project Managers

✔️ Strong leadership and people management skills

✔️ Excellent knowledge of Agile methodologies, Scrum & Kanban frameworks

✔️ Upper-Intermediate or higher spoken and written English
 

Could be a plus:

✔️ PMP, PgMP, PSM, SAFe or equivalent certifications

✔️ Experience working in outstaffing / outsourcing companies

Daily and Monthly Responsibilities:

✔️ Supervising and mentoring Project Managers across multiple projects

✔️ Ensuring consistent delivery standards and operational excellence across the program

✔️ Managing team performance and supporting professional growth

✔️ Aligning project execution with strategic business objectives

✔️ Monitoring, forecasting, and reporting program delivery status

✔️ Managing risks, dependencies, and escalations across projects

✔️ Coordinating cross-functional teams and improving delivery processes

✔️ Maintaining high-level program documentation and reporting

✔️ Driving continuous improvement initiatives within delivery teams
 

What we offer:

✅ Fully remote work

🏝 18 vacation days per year

🎁 Birthday gifts

📚 Opportunities for learning and growth through challenging tasks

🚀 Work with international clients and ambitious long-term projects

👋 Hey!
 

We’re looking for an experienced Product Owner to join our dynamic and highly skilled team, working on an exciting Gambling project!
 

We’re a young and ambitious outstaffing company that builds strong, dedicated teams for long-term collaboration with international clients. We value responsibility, talent, and a growth mindset.
 

🟢 Full Remote
🕘 Working hours: 9:00–18:00
 

🔧 What you’ll be doing:

• Manage Product Backlog: Prioritize and organize tasks to meet business objectives.
• Define Sprint Objectives: Shape sprint goals based on strategic priorities.
• Approve Deliverables: Review and verify completed work from design to release.
• Communicate with Stakeholders: Act as the key link between the dev team and business stakeholders.
• Support Agile Processes: Facilitate Scrum and Agile practices within the team.
   

📌 What we’re looking for:

• 3+ years in a Product Owner or related role (Business Analyst, System Analyst, QA Analyst)
• Strong understanding of:
  • Requirements lifecycle and backlog management
  • Product development architecture and software processes
  • Agile/Scrum methodologies
  • UX principles
• Bonus: basic knowledge of coding or UI/UX design
• English level: B2
   

🎁 What we offer:

✅ Full Remote work
🏝 18 vacation days per year
📚 Learning opportunities & engaging, challenging tasks
💥 Medical insurance
 

🚀 Ready to shape great products? Apply now!

We are looking for an Integration Team Lead to own the architecture and reliability of our advertising platform integrations while leading a small engineering team and driving the integration roadmap. In this role, you will design and scale data pipelines that process large volumes of advertising data, ensure stable data synchronization across external marketing platforms, and lead new integration initiatives from API evaluation to production rollout. You will play a key role in shaping the platform’s integration strategy, mentoring engineers, and building scalable, AI-enabled integration solutions that power our core data infrastructure.

Requirements
- 5+ years in backend/data engineering, including 2+ years working with advertising/marketing APIs.
- Hands-on experience with Meta Marketing API and/or LinkedIn Marketing API: real work with rate limits, async reports, breakdowns, attribution windows.
- Strong Python skills: production-grade code with error handling, logging, and tests.
- Experience leading a team (2+ people): code reviews, task planning, growing engineers.
- Solid understanding of data pipeline patterns: idempotency, backfill, incremental sync, schema evolution.
- Experience with GCP or comparable cloud (AWS/Azure) at the service design level.

- Actively use AI-assisted development tools (e.g., Copilot, Cursor, Claude Code) in daily engineering workflows for code generation, debugging, documentation, and data pipeline design, applying sound engineering judgment when validating AI-generated outputs.

Nice to Have
- Knowledge of the Programmatic ecosystem: DV360, The Trade Desk, OpenRTB.
- Experience with BigQuery and/or ClickHouse.
- Pulumi / Terraform for IaC.
- Understanding of advertising metrics: impressions, clicks, conversions, ROAS, attribution models.

Responsibilities
- Own the architecture and evolution of all platform integrations: Meta Marketing API, LinkedIn Marketing API, Programmatic channels (DV360, The Trade Desk, etc.).
- Lead a team of 2-4 engineers: code reviews, sprint planning, mentorship.
- Design and maintain data pipelines: Ad Platform APIs to BigQuery/ClickHouse via Cloud Run Jobs and n8n workflows.
- Ensure data sync reliability: monitoring, alerting, error handling, retry strategies.
- Work with API rate limits, OAuth flows, and webhooks across advertising platforms - Drive new integration projects from API evaluation through production rollout. 
- Collaborate with the product team to prioritize the integration roadmap.

What We Offer

- Fully remote with flexible hours (aligned with EU timezones for syncs).
- Influence on the quality assurance strategy across the entire engineering department.
- A cross-team role with visibility into every part of the product.
- AI-first tooling.
- Claude Code licenses and cutting-edge AI development workflows. 
- A team with no bureaucracy, decisions are made fast.

We are looking for a Senior Data Engineer. This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.

The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.

What you will do:

• Design and maintain scalable data pipelines in Python on Google Cloud Platform
• Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
• Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
• Maintain high-load orchestration with custom Python nodes and complex workflows
• Own deployment and release processes (CI/CD)
• Optimize PostgreSQL performance under heavy load
• Investigate incidents and resolve root causes permanently

• Use AI engineering tools such as Claude in daily development

   

Requirements:

• 4+ years of experience in Data Engineering / Backend Engineering
• Strong Python skills
• Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
• Strong knowledge of GCP (Cloud Functions, IAM, Networking)
• Experience with BigQuery, Spark, Iceberg
• Good understanding of Kubernetes
• Experience with workflow orchestration tools (n8n is a strong plus)
• Strong practical knowledge of PostgreSQL

• English level B2+

   

What is important for us:

• Ownership mindset
• Fast learning ability
• Strong problem-solving approach
• Active AI usage in engineering work
• Focus on practical results over unnecessary complexity

We are looking for a Senior Data Engineer. This is not a standard ETL role. You will work on a high-load system processing 10,000+ executions per minute, building scalable pipelines where AI and LLM logic are embedded directly into production data flows.

The role combines data engineering, backend thinking, infrastructure ownership, and real production AI integration.

What you will do:

• Design and maintain scalable data pipelines in Python on Google Cloud Platform
• Build and optimize AI-driven scoring flows using LLMs for real-time identity enrichment
• Work with BigQuery, Apache Spark, and Apache Iceberg for heavy data processing
• Maintain high-load orchestration with custom Python nodes and complex workflows
• Own deployment and release processes (CI/CD)
• Optimize PostgreSQL performance under heavy load
• Investigate incidents and resolve root causes permanently

• Use AI engineering tools such as Claude in daily development

   

Requirements:

• 4+ years of experience in Data Engineering / Backend Engineering
• Strong Python skills
• Commercial experience with production LLM integration (OpenAI / Anthropic / Gemini)
• Strong knowledge of GCP (Cloud Functions, IAM, Networking)
• Experience with BigQuery, Spark, Iceberg
• Good understanding of Kubernetes
• Experience with workflow orchestration tools (n8n is a strong plus)
• Strong practical knowledge of PostgreSQL

• English level B2+

   

What is important for us:

• Ownership mindset
• Fast learning ability
• Strong problem-solving approach
• Active AI usage in engineering work
• Focus on practical results over unnecessary complexity

We are looking for a skilled Middle Manual QA Engineer.

✅ Requirements:

✔️ 2+ years of related work experience

✔️ Solid knowledge of testing processes, methodologies, and standards

✔️ Experience in web projects testing

✔️ Experience in defining scope of testing, developing testing approach

✔️ Attentive to detail, analytical skills, and a scientific approach to problem-solving

✔️ Basic SQL knowledge

✔️ Strong verbal/written communication & an excellent attention to detail

✔️ Knowledge of JIRA and/or similar bug tracking tools

✔️ Experience in test documentation creation and maintenance experience in defining scope of testing, test plan, writing test cases,

✔️ Intermediate+ level of English (both verbal and written)

✅ Will be a plus 

✔️ Experience in I18n,l10n testing 

✔️ Experience in API testing

✔️ Knowledge of Azure Data Factory

✅ Duties and opportunities

✔️ Manual testing of web applications

✔️ Defects management in the bug-tracking system

✔️ Test documentation management

✔️ Collaboration with project team

 We are looking for a Senior Data Analyst to join our Identity team.

This is not a classic BI/dashboard role. You will work on large-scale identity resolution, AI scoring systems, data quality, and product decision-making.

We process 70+ TB of data and run 20M+ enrichment operations daily across multiple data sources.

You will work directly with Product and Engineering and own analytics for one of the core business domains.
 

🟢 What You’ll Do

• Build frameworks to measure data quality, match rates, AI scoring accuracy, ROI
• Analyze and improve LLM-based scoring systems together with engineers
• Compare external data providers and identify highest-value sources
• Investigate mismatched / conflicting data across systems
• Support internal teams with audience, campaign, and performance analysis
• Detect pipeline or provider quality issues early and drive fixes
• Turn ambiguous business questions into clear decisions
   

🟢 Requirements

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team — not consultancy, not BI-only roles.
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. Can read and write complex queries on tens of terabytes without someone pre-modelling the data.
• Python for analysis at a working level — pandas, Jupyter, or equivalent. Can write a small script or helper when an existing tool doesn't cover the case.
• Built measurement or evaluation frameworks from scratch for systems with no baseline — candidate defined what to measure and how, not consumed someone else's KPI.
• Comfort with probabilistic systems — understands noise, ranking, scoring, and that 100% accuracy is not a goal.
• AI-native workflow — uses Claude Code, ChatGPT, Copilot, or similar AI tools daily in their process.
• English: B2+ (Upper-Intermediate) or higher.
   

🟢 Strong Plus

• LLM evaluation / prompt testing
• Identity graph / AdTech / MarTech experience
• Healthcare / pharma data experience
• A/B testing / experimentation
   

🟢 We Offer

• Fully remote
• Flexible hours (CET ±2 overlap)
• High ownership / direct impact
• AI-native environment
• Fast decisions, low bureaucracy

We’re looking for an experienced Senior Graphic Designer to join our

development team! You’ll work alongside a highly skilled group

on an exciting Gambling project.

 Requirements:

- 5+ years of professional experience in creative studio teams,

preferably in branded graphic illustrations and visual solutions.

- Experience in photo retouching, photography, AI-generated

images, typography, vector graphics, and logo design.

- Ability to scale a brand’s graphic concept into a comprehensive

library of promotional materials.

- Strong proficiency in Figma and Photoshop; excellent skills in

retouching and color correction are required.

- Knowledge of basic UI principles and stages of the product

design process; experience collaborating with product design

teams.

- Experience creating and managing graphic asset libraries and

style guides.
 

 Responsibilities:

- Create high-quality promotional designs aligned with the

visual concept, using various Adobe, AI, and 3D tools. 

- Review graphic materials to ensure they meet quality standards

and align with the visual concept

We are looking for a Senior Data Analyst to join our global team. This is not a standard analyst role. We are building a dynamic identity resolution system where AI is deeply integrated — both as a productivity multiplier and as a core component of our data processing logic for identity resolution and LLM-based scoring.

We run enrichment against 70+ TB of data, apply AI and LLM-based scoring on top, and process around 20 million enrichment operations per day across hundreds of thousands of records.

The analytical challenges ahead are substantial: how to measure the quality of AI-driven scoring, how to validate that a change makes the system better, how to know where our money and time deliver the most value, and how to turn the questions our internal teams bring in into fast data-backed answers. You will own this side of the business, working daily alongside engineers and the product lead to turn these challenges into decisions that ship.

The main part of the role is not building dashboards — it is the data work that makes a meaningful dashboard possible in the first place.

 Concretely, you will be:

• Looking at data from multiple vendors side by side and deciding what to trust.
• Reconciling entities across sources that have different shapes and quality.
• Proposing and validating the logic that matches and scores them.
• Defining metrics and ground truth for questions nobody has asked before.
• Tracing why numbers don't line up across partial and sometimes contradictory sources.
  
  Responsibilities:
• Measurement & Evaluation Foundations: Define how we measure what matters — data quality, the accuracy of our AI scoring, how many records actually get matched to usable signals, cost per outcome. Build the feedback loops that tell us whether a change makes the system better or worse.

• Scoring Intelligence (co-owned with engineers): Partner with the engineering team on the LLM-based scoring system. You will build the evaluation framework for AI scoring, run experiments comparing prompts, models, and approaches against a baseline, and make data-backed calls on where we invest next. Our AI scoring system is actively evolving — you will shape how we measure and improve it.

• Client-related Analysis: Own the analytical side of the work that internal sales and media-buying teams bring in from pharma clients — how reachable a target audience is, how good the data looks, why a campaign performed the way it did. You turn their questions into data-backed answers they can use. Identity is a product core; the analyst works with internal teams, not with clients directly.

• Cost and Value Analysis: Turn cost and value into product decisions. Which data sources and enrichment scenarios pay off, where we overspend, what to cache, what to cut. We operate a mix of free owned data and paid external providers — the decisions have real dollar impact.

• Active AI Usage: Use Claude Code and modern AI engineering tools to multiply your own output. Automate the repetitive parts of analysis so you can focus on the decisions. We provide Claude Code licenses and expect active daily use.

• Data Quality Response: When pipeline output drifts, a provider degrades, or upstream data shifts, you notice first, diagnose the root cause, and drive the fix. You treat data quality as a product, not a ticket queue.
   

Requirements:

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team (not consultancy, not BI-only roles).
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. You can read and write complex queries on tens of terabytes without someone pre-modelling the data for you.
• Python for analysis at a working level — pandas, Jupyter, or modern equivalents. Comfortable putting together a small script or helper when an existing tool doesn't cover your case.
• Built measurement or evaluation frameworks from scratch for systems that had no baseline. You are comfortable defining what and how to measure, not consuming someone else's KPI.
• Comfort with probabilistic systems. You understand that noise is inherent and 100% accuracy is not the goal — scoring, matching, ranking.
• AI-native workflow. You already use Claude Code, ChatGPT, Copilot, or similar AI tools daily and integrate them into your analytical process.
• English: B2+ (Upper-Intermediate) or higher.

Strong plus (one or more)

• LLM evaluation experience — A/B testing AI-powered features, output scoring, prompt iteration with measurable outcomes.
• Identity resolution / identity graph experience — adtech, martech, or customer data platform context (LiveIntent, LiveRamp, Epsilon, Experian Marketing, Acxiom, Merkle, or similar).
• Healthcare or pharma data — working with NPI, HCP-level data, healthcare taxonomies, pharma targeting.
   

Nice to have:

• Experience running controlled experiments on data pipelines.
• Prompt engineering or structured LLM prompt design.
• Prior work in AI-first product companies.

Culture & Mindset

• Self-improvement: You are a fast learner. You don't fear AI replacing you; you master it to replace your manual tasks.
• Ownership: You treat the Identity domain as your own business. If scoring quality drifts or a provider degrades, you notice it and drive the fix without being asked.
• Internal Locus of Control: You take responsibility for outcomes. If external data shifts or an API changes, you build around it instead of blaming the provider.
• Get It Done: You prioritize shipping answers. You know when to send a rough estimate and when to build a proper framework.

Openness: You share findings and admit mistakes openly — both wins and failures travel across the team. If you spot a better way to do something, you volunteer it without being asked.

We are looking for a Senior Data Engineer to join our team. This is not a standard ETL role. We are building a dynamic data ecosystem where AI is deeply integrated - both as a productivity multiplier and as a core component of our data processing logic for identity data enrichment and data scoring.

You will own the infrastructure that handles over 10,000 executions per minute, ensuring stability, scalability, and data integrity. You will work with a modern stack on Google Cloud Platform, utilizing Cloud Functions and Kubernetes.

We are looking for an engineer who improves infrastructure, automates everything, and is eager to implement LLM-based logic directly into high-load data flows.

Responsibilities

• AI-Driven Data Scoring: Design and implement pipelines that utilize LLMs to analyze and score identity data in real-time. You will integrate AI models directly into the decision-making loop, balancing accuracy with latency and cost.
• Own the Data Architecture: Architect scalable data solutions using GCP and Python. You will manage data storage and retrieval using BigQuery and Apache Iceberg to support querying of TBs of data.
• Heavy Data Processing: Utilize Apache Spark for data transformations and batch processing when lightweight cloud functions are not enough.
• Manage High-Load Orchestration: Maintain and optimize our system instances. It involves complex dataflows, custom Python nodes, and performance tuning for 10k+ execs/minute.
• Release Lifecycle (CI/CD): Take ownership of the deployment process, ensuring that updates to pipelines and infrastructure are released safely with proper testing and rollback strategies.
• Database Optimization: Manage PostgreSQL performance under heavy load, optimizing complex queries and indexing strategies.
• Active AI Usage: Use Claude Code and other AI engineering tools to accelerate your own development, refactoring, and testing processes.
• Incident Resolution: Proactively monitor the system. When alerts fire, you investigate the root cause—whether it’s a database lock or an LLM hallucination—and fix it permanently.
   

Requirements

• 4-5+ years of experience in Data Engineering or Backend Engineering with a strong data focus.
• Production AI Integration: Experience integrating LLMs (OpenAI, Anthropic, Gemini) into production applications via API. You understand latency, token limits, and how to structure data for AI scoring.
• Expertise in GCP: Understanding of Google Cloud Platform (Cloud Functions, IAM, Networking).
• Strong Python: You write clean, efficient, and testable code. You are comfortable building custom logic where standard tools fall short.
• Big Data Stack: Experience with BigQuery, Apache Spark, and modern table formats like Apache Iceberg.
• Kubernetes (K8s): Experience deploying and scaling services in containerized environments.
• Workflow Automation: Understanding of workflow orchestration tools at a deep technical level. N8N is a big part of our domain, so familiarity with it is highly valuable.
• PostgreSQL Mastery: Proven ability to handle heavy write/read loads and optimize schemas.
• English: B2+ (Upper-Intermediate) or higher.
   

Culture & Mindset

• Self-improvement: You are a fast learner. You don't fear AI replacing you; you master it to replace your manual tasks.
• Ownership: You treat the Identity domain as your own business. If a scoring model drifts or a pipeline slows down, you notice it and fix it without being asked.
• Internal Locus of Control: You take responsibility for outcomes. If an external API fails, you build a fallback mechanism instead of just blaming the provider.
• Get It Done: You prioritize shipping value. You know when to use a simple script and when to build a complex architecture.

Openness: You share knowledge freely. If you find a better way to prompt the AI for scoring, you share it with the team.

We are looking for an Integration Team Lead to own the architecture and reliability of our advertising platform integrations while leading a small engineering team and driving the integration roadmap. In this role, you will design and scale data pipelines that process large volumes of advertising data, ensure stable data synchronization across external marketing platforms, and lead new integration initiatives from API evaluation to production rollout. You will play a key role in shaping the platform’s integration strategy, mentoring engineers, and building scalable, AI-enabled integration solutions that power our core data infrastructure.

Requirements
- 5+ years in backend/data engineering, including 2+ years working with advertising/marketing APIs.
- Hands-on experience with Meta Marketing API and/or LinkedIn Marketing API: real work with rate limits, async reports, breakdowns, attribution windows.
- Strong Python skills: production-grade code with error handling, logging, and tests.
- Experience leading a team (2+ people): code reviews, task planning, growing engineers.
- Solid understanding of data pipeline patterns: idempotency, backfill, incremental sync, schema evolution.
- Experience with GCP or comparable cloud (AWS/Azure) at the service design level.

- Actively use AI-assisted development tools (e.g., Copilot, Cursor, Claude Code) in daily engineering workflows for code generation, debugging, documentation, and data pipeline design, applying sound engineering judgment when validating AI-generated outputs.

Nice to Have
- Knowledge of the Programmatic ecosystem: DV360, The Trade Desk, OpenRTB.
- Experience with BigQuery and/or ClickHouse.
- Pulumi / Terraform for IaC.
- Understanding of advertising metrics: impressions, clicks, conversions, ROAS, attribution models.

Responsibilities
- Own the architecture and evolution of all platform integrations: Meta Marketing API, LinkedIn Marketing API, Programmatic channels (DV360, The Trade Desk, etc.).
- Lead a team of 2-4 engineers: code reviews, sprint planning, mentorship.
- Design and maintain data pipelines: Ad Platform APIs to BigQuery/ClickHouse via Cloud Run Jobs and n8n workflows.
- Ensure data sync reliability: monitoring, alerting, error handling, retry strategies.
- Work with API rate limits, OAuth flows, and webhooks across advertising platforms - Drive new integration projects from API evaluation through production rollout. 
- Collaborate with the product team to prioritize the integration roadmap.

We are looking for a Senior Data Analyst to join a team building an AI-powered identity data platform.

This is not a classic reporting role. You will work on complex data problems: measuring AI scoring quality, validating matching logic, analyzing provider performance, and helping Product & Engineering make better decisions.

We process large-scale datasets, integrate multiple external data sources, and run millions of enrichment operations daily. Your work will directly impact product quality, efficiency, and growth.

Responsibilities:

• Build metrics for data quality, match rates, scoring accuracy, and business impact
• Analyze performance of AI / LLM scoring models together with engineers
• Compare external data providers and identify best ROI sources
• Investigate anomalies, pipeline issues, and mismatched numbers
• Support internal teams with fast, data-backed analysis
• Create dashboards when needed — but focus mainly on the logic behind them
• Use AI tools to automate repetitive analytical work
   

Requirements:

• 5+ years in Data Analytics / Product Analytics / Data Science
• Strong SQL (BigQuery, Snowflake, Redshift or similar)
• Experience working with large datasets
• Python for analytics (pandas, notebooks, scripts)
• Experience defining KPIs or measurement frameworks from scratch
• Strong analytical thinking and ownership mindset
• Comfortable working with probabilistic / imperfect data systems
• Daily use of AI tools like ChatGPT, Claude, Copilot, etc.
• English B2+

Nice to Have:

• Experience with LLM evaluation or AI product analytics
• Identity resolution / entity matching experience

• AdTech / MarTech / Healthcare data background

   

What We Offer:

• Fully remote
• Flexible hours with CET overlap
• High-impact product role
• Direct collaboration with Product & Engineering leads
• AI-first working environment
• Fast decisions, no bureaucracy