Equals 5

We are looking for a Team Lead who will take ownership of the architecture and technical evolution of our web platform, while leading a small team of full-stack engineers. In this role, you will be responsible for the full delivery cycle  from database design and REST API architecture to building modern Vue.js interfaces ensuring scalability, performance, and maintainability of the system. You will establish engineering standards, mentor developers, and shape the platform’s direction through thoughtful architectural decisions, performance optimization, and gradual modernization of legacy code. This is a high-impact role with cross-team collaboration, fast decision-making, and an AI-first approach to development.

Requirements
- 5+ years of full-stack web development experience with PHP and JavaScript
- Deep knowledge of Laravel: Eloquent, queues, events, middleware, service providers, testing with PHPUnit/Pest.
- Strong frontend skills with Vue.js 3 (Composition API, Pinia, Vue Router) and TypeScript.
- Experience leading a team (2+ people): code reviews, task planning, growing engineers, establishing standards.
- Solid understanding of relational database design and PostgreSQL: query optimization, migrations, indexing strategies.
- Experience with REST API design: versioning, error handling, authentication (JWT/OAuth), pagination.
- Familiarity with Docker and CI/CD pipelines.

Nice to Have
- Experience with GCP or comparable cloud (AWS/Azure) at the service level. 
- Knowledge of Vite build tooling, SSR, or micro-frontend patterns.
- Experience with real-time features (WebSockets, broadcasting).
- Familiarity with Pulumi / Terraform for IaC.
- Understanding of healthcare / pharma ad-tech domain.
- Experience with Playwright or Cypress for E2E testing.

Responsibilities
Own the architecture and technical direction of the web platform (Laravel backend + Vue.js frontend).
- Lead a team of 2-3 full-stack engineers: code reviews, sprint planning, mentorship, and career development.
- Drive feature delivery end-to-end: from API design and database schema to Vue.js components and user experience.
- Ensure code quality, test coverage, and maintainability across the full stack.
- Design and evolve the REST API layer: versioning, authentication, rate limiting, and documentation.
- Optimize application performance: query tuning, caching strategies, frontend bundle optimization.
- Collaborate with Product and Design to translate requirements into well-architected, scalable solutions.
- Manage technical debt and drive incremental modernization of legacy code.
 

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 an Integration Tech Lead to take full ownership of one of the most business-critical areas of our platform — integrations. This role sits at the intersection of backend engineering, data flows, and external platform connectivity.

You will be responsible not only for building and scaling integrations, but also for ensuring their reliability, stability, and overall performance. This is a high-impact role where failures directly affect business outcomes, so we are looking for someone who can take end-to-end responsibility and confidently drive technical decisions.

In this role, you will lead a small team, bring structure to an evolving domain, and define how integrations are designed, built, and maintained across the platform.

Requirements

• 5+ years of experience in backend, platform, or data engineering.
• Experience in backend development using at least one programming language (such as Python, PHP, C#, or similar), with a willingness to work in a multi-stack environment.
• Strong experience working with APIs and integrations (design, implementation, maintenance).
• Experience working with marketing or advertising platforms (Meta, LinkedIn, programmatic ecosystem).
• Proven experience working with complex technical systems and driving them to a stable state.
• Experience leading or mentoring engineers.
• Solid understanding of distributed systems and data flows.
• Experience working with production systems where reliability and uptime are critical.
• Strong engineering mindset: ability to make decisions, prioritize, and take responsibility.
• Experience using AI-assisted development tools (Copilot, Cursor, Claude Code) in daily workflows, with the ability to critically evaluate outputs.

Nice to Have

• Experience in Data Engineering (data pipelines, ETL/ELT processes, data synchronization).
• Experience with cloud platforms (GCP, AWS, or Azure).
• Understanding of high-load systems or large-scale data processing.

Responsibilities

• Take full ownership of the integrations domain across the platform.
• Define and drive integration architecture and technical direction.
• Lead a small team of engineers: code reviews, mentorship, and development.
• Ensure reliability of integrations: monitoring, alerting, error handling, and recovery strategies.
• Drive integration projects end-to-end: from API evaluation to production rollout.
• Improve and stabilize existing integrations and data flows.
• Collaborate with product and business teams to define priorities.
• Bring structure and leadership to a currently evolving area.

What We Offer

• Fully remote with flexible hours (aligned with EU time zones).
• High-impact role with direct influence on core business processes.
• Ownership and autonomy in technical decision-making.
• Fast-paced environment with minimal bureaucracy.
• AI-first engineering culture and modern tooling.
• Opportunity to shape and scale a critical part of the platform.

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 to join the Identity team at Equals5. 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.
   

What We Offer

• Fully remote with flexible hours (aligned with EU timezones for syncs).
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech for both daily coding and product features.
• High-Impact Role: You will directly influence how we identify and score users, impacting the core business logic.
• Cross-functional visibility: Work closely with Product and Tech Leads to shape the future of Identity.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.

Equals5 helps pharmaceutical companies run precisely targeted ad campaigns on social platforms by identifying healthcare professionals and the consumer signals that reach them. The Identity team builds the data, scoring, and targeting systems that make this possible.

We are looking for a Data Analyst  to join the Identity team at Equals5. 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 

• 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.

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.

We are looking for a Data / Backend Engineer to architect and scale the core data infrastructure behind our healthcare marketing platform. In this role, you will design high-throughput data systems that process millions of behavioral events, power real-time attribution and user scoring, and enable precise targeting of healthcare professionals across 20+ channels.

You will work at the intersection of data engineering, backend systems, and marketing infrastructure, building scalable pipelines, tracking systems, and APIs that support analytics, segmentation, and campaign activation. The role also involves experimenting with AI-powered automation and agent-based workflows to improve internal operations and product capabilities.

This is a high-ownership position where you will shape architecture decisions, build critical platform components from the ground up, and help evolve our data platform as the company scales.

Responsibilities

- Architect and own data-heavy backend systems powering real-time attribution, user modeling, and scoring

- Build and evolve client-side tracking pixels (like FB pixel / Amplitude snippet / Heap autocapture) from scratch

- Set up and manage scalable ETL workflows: cleaning, merging, enriching, splitting, transforming across millions of behavioral events
Lead the build of CDP / CDXP-style data layers to support segmentation, scoring, and activation across channels

- Connect and compose systems using modern low-code / no-code tools (n8n) to accelerate ops

- Implement and maintain high-availability APIs for analytics, scoring, and campaign delivery

- Drive experimentation around AI-powered agents and automation tools that can boost internal workflows

Requirements

- System Design & Data Architecture:
Designs scalable, event-driven data platforms with strong decoupling, fault tolerance, and horizontal scalability. Builds real-time and batch pipelines using lakehouse architectures and streaming systems (Kafka / PubSub).

- Distributed Data Processing (Spark / BigQuery / Iceberg):
Expert in large-scale data processing, query optimization, and cost-efficient analytics. Deep understanding of Spark execution, partitioning, and modern table formats (Iceberg / Delta).

- Cloud & Infrastructure (GCP / Kubernetes):
Builds resilient cloud-native data platforms on GCP and Kubernetes using IaC, autoscaling, and secure access (IAM, Workload Identity).

- Python Engineering:
Develops high-performance Python services for data and ML workloads with focus on concurrency, clean architecture, and production-grade quality.

- Databases & Performance (PostgreSQL / OLTP):
Optimizes high-throughput OLTP systems through indexing, partitioning, and query analysis (EXPLAIN ANALYZE, MVCC).

- Reliability & Observability (SRE):
Implements resilient data systems with idempotency, retries, observability, SLOs, and incident management.

- AI / LLM Integration:
Integrates LLMs into production pipelines with structured outputs, caching, batching, prompt versioning, and evaluation.

- Workflow Orchestration (Airflow / Dagster):
Designs scalable DAG-based workflows with dependency management, retries, and reproducible backfills.

- CI/CD & DevOps for Data:
Implements safe deployments for data systems including schema migrations, canary releases, and data contracts.

- Ownership & Engineering Maturity:
Owns end-to-end production systems and architecture decisions while balancing delivery speed, quality, and technical debt.

Nice-to-have: 

- Experience in MarTech / AdTech platforms (e.g., DSPs, attribution systems, DMP/CDP tools)

- Deep knowledge of data matching/fingerprinting techniques (identity graphs, IP + UA resolution, hashed PII workflows)

- Strong prompt engineering skills — not just ChatGPT 101, but chaining, system prompting, tooling integration

What We Offer
- Fully remote with flexible hours (aligned with EU timezones for syncs).
- Influence on quality strategy across the entire engineering organization.
- 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 QA Team Lead who will be responsible for quality assurance across multiple engineering teams and play a key role in building a scalable testing strategy. You will act as the quality owner for the larger development team, ensuring the reliability of the entire product data flow from external API integrations to end-user dashboards.

In this role, you will lead the QA team and work closely with engineering team leads, implementing automation, quality gates, and testing best practices within development workflows. You will have the opportunity to shape the company-wide quality strategy, scale automation efforts, and influence product quality across the entire engineering organization.

Responsibilities
- Lead a QA team of 3–4 engineers, including task assignment, code reviews, mentorship, and supporting professional growth.
- Own end-to-end quality across all engineering teams.

- Build and maintain a cross-team testing strategy covering the full data flow — from API ingestion through data pipelines to the end-user dashboard.
- Design and implement automated test suites, including E2E (Playwright/Cypress), API, integration, and regression tests.
- Establish quality gates in CI/CD pipelines, ensuring no code is released without passing automated checks.
- Coordinate release testing across teams, ensuring that changes in one system do not impact downstream consumers.
- Define and track quality metrics, such as test coverage, defect rates, time-to-detection, and regression frequency.
- Collaborate closely with team leads (Platform, Integrations, etc.) to embed quality practices into development workflows.
- Manage test environments and test data, ensuring realistic and reproducible testing scenarios across all domains.

Requirements
- 5+ years of experience in QA/SDET, including 2+ years in a leadership role managing a QA team.
- Strong experience with test automation, using Playwright, Cypress, or similar E2E frameworks.
- Experience testing APIs (REST), both manual and automated, including contract and integration testing.
- Understanding of data pipeline testing, including validation of data flow from source APIs through transformation layers to analytics systems.
- Ability to work across multiple tech stacks (PHP/Laravel, Vue.js, Python, SQL). You are not required to be a developer, but you should be able to read and understand code.
- Experience with CI/CD integration, embedding automated tests into build pipelines and managing test environments.
- Strong communication and stakeholder management skills — you will coordinate with 3–4 team leads and communicate quality status clearly.

Nice to Have
- Experience with BigQuery and/or ClickHouse data validation.
- Knowledge of advertising/marketing tech domain (Meta API, LinkedIn API). 
- Experience with performance/load testing (k6, Locust, Artillery).
- Familiarity with GCP services (Cloud Run, Cloud SQL, Cloud Scheduler).
- Understanding of healthcare/pharma compliance requirements.
- Experience with visual regression testing.

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.