UPPeople

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.

Our client is a product company that develops a data-driven advertising platform focused on the healthcare and pharmaceutical industry. The platform enables companies to launch and manage marketing campaigns across multiple digital channels, collect detailed user-level data, and optimize performance using advanced targeting and analytics.

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 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
• Strong Python skills (production-grade code, error handling, logging, tests)
• Team leadership experience (2+ engineers)
• Solid understanding of data pipelines (idempotency, backfill, incremental sync, schema evolution)
• Experience with GCP or AWS/Azure
• Experience using AI tools (Copilot, Cursor, Claude Code) in engineering workflows

Nice to have

• Programmatic ecosystem knowledge (DV360, The Trade Desk, OpenRTB)
• BigQuery / ClickHouse
• Terraform / Pulumi
• Understanding of ad metrics (ROAS, attribution, etc.)

Responsibilities

• Own integrations architecture (Meta, LinkedIn, Programmatic platforms)
• Lead a team of 2–4 engineers
• Design and maintain data pipelines (APIs → BigQuery/ClickHouse)
• Ensure reliability (monitoring, alerting, retries)
• Work with OAuth, rate limits, webhooks
• Drive integrations from idea → production
• Collaborate with product team

What we offer

• Fully remote, flexible hours
• Strong impact on product & engineering decisions
• Cross-functional visibility
• AI-first engineering environment
• Fast decision-making, no bureaucracy

The company is building a healthcare-focused adtech platform that enables precise targeting of healthcare professionals using large-scale data and AI.

We’re looking for a Senior Data Analyst to define how we measure data quality, evaluate AI/LLM-based scoring, and generate insights that support product, sales, and media buying teams. You’ll work with 70+ TB of data, design evaluation frameworks from scratch, and help optimize performance, cost, and data pipelines.

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.

 We’re  looking for a Senior Product Manager to lead our ad network integrations and channel expansion strategy.

This role is ideal for someone with strong hands-on media buying experience who understands how campaigns work end-to-end — from setup to optimization and attribution — and can translate that into scalable product solutions.

What you’ll do:
• Own product strategy and roadmap for ad platform integrations
• Build and optimize connections with Facebook, LinkedIn, TikTok, X, and more
• Drive automation, real-time data sync, and performance reporting
• Lead a cross-functional team (engineering, data, QA)
• Turn business & media buying needs into powerful product features

What we’re looking for:
• 5+ years in Product Management (AdTech / MarTech)
• Hands-on media buying experience (must-have)
• Strong understanding of paid social, attribution, and campaign performance
• Experience with APIs, integrations, and data-driven products
• AI-first mindset and experience using AI tools in workflows

Nice to have: 
Programmatic advertising (DSP, SSP, ad exchanges)
Pharma / healthcare marketing experience
Healthcare professional targeting, NPI data
Automation technologies
AI agents and AI-driven workflows

Join us to build a platform that connects media buying, data, and performance into one ecosystem.

Equals5 is a leading Healthcare Marketing SaaS for Pharma and Life Sciences. Our platform leverages exclusive NPI-level targeting technology to help brands reach healthcare professionals across 20+ channels with precise, user-level reporting.

The Role

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.