Location: Remote (India or UK preferred)
Type: Full-Time | Permanent
Tech: Python, SQL, Spark, Airflow, dbt, Kafka/Kinesis/SQS, AWS, Terraform/CDK, modern ETL
Comp: Competitive salary + meaningful equity

Why This Role Exists

PubX builds publisher-first agentic advertising infrastructure — AI that makes real-time, revenue-critical pricing decisions for digital publishers. Our dynamic floor pricing engine uses machine learning to optimize every programmatic ad auction individually, generating measurable revenue uplift for publishers. We’re ranked #5 globally in Prebid Analytics Adapter Rankings, and growing.

The problem we’re solving

Digital publishers leave significant revenue on the table because ad pricing is still largely static or rule-based. Every ad impression is unique, but most pricing systems treat them the same. PubX’s AI analyzes bid-stream data and historical patterns to set optimal price floors per auction, in real-time. As we expand into agentic AI systems, we’re building the next generation of autonomous advertising infrastructure.

About us

We’re a ~25-person, fully remote team founded in 2020 by Andrew Mole (CEO) and Alex Rosen (CTO), who previously built Platform360 — a machine-learning powered DSP — giving them a decade of deep AdTech experience. We’re seed-funded, profitable in our core product, and growing our engineering team with a strong presence in India and UK leadership. Our investors include Concept Ventures, Haatch, and Force Over Mass Capital.

The Role

As a Senior Data Engineer, you’ll own the data foundations behind our agentic AI products. This means building and operating high-throughput batch and streaming pipelines, scalable storage and modeling layers, and reliable datasets that power real-time decisioning, analytics, and ML workflows. You’ll work across event ingestion, enrichment, aggregation, and serving — dealing with the kind of volume and latency constraints that make AdTech data engineering genuinely interesting.

You’ll collaborate closely with product, data science, and operations in a distributed team, contributing to both day-to-day delivery and longer-term architectural decisions. This role has a clear path to evolve into a Tech Lead position for one of our product teams.

What You’ll Work On

• Design and maintain high-volume data pipelines (batch + streaming) powering agentic AI features and core product workflows
• Build event-driven components using Kafka and message queues, including idempotency patterns, replay strategies, and backfill mechanisms
• Develop data models and transformation layers (lakehouse patterns, dbt-style modeling) supporting both analytics and ML/AI consumption
• Own data quality and reliability: schema management, validation, lineage, SLAs, and incident response
• Enable AI/ML workflows with robust datasets for training, evaluation, feature generation, and feedback loops from production agents
• Deploy and operate data infrastructure on AWS using infrastructure-as-code

What We’re Looking For

We’re looking for an experienced engineer who has worked on production systems and enjoys solving practical problems with AI.

You’ve likely have:

• Strong data engineering fundamentals: data modeling, partitioning, performance tuning, and cost-aware design for high-volume workloads
• Experience building streaming and event-driven systems (Kafka/queues), including handling late/out-of-order events, backfills, and real-world data edge cases
• Strong SQL + Python skills, and comfort with modern data stack tooling (e.g., Spark, Airflow/Dagster, dbt, warehouse/lakehouse patterns)
• Hands-on AWS experience with production operations for data systems: monitoring, incident response, and security considerations (PII, access control, encryption, auditability)
• Familiarity integrating data with AI/ML and agentic systems: feature pipelines, evaluation datasets, grounding/citations inputs, and feedback capture from agent outcomes

You tend to:

• Make pragmatic decisions balancing speed, quality, cost, and risk trade-offs.
• Communicate technical ideas well in writing and conversation to both technical and non-technical audiences.
• Write clean, well-tested code with thoughtful abstractions that’s easy to extend and operate.
• Learn quickly when things are unfamiliar by prototyping, then hardening and documenting what you ship.

Bonus (not required):

• Experience with AdTech or other high volume real-time systems

Who This Role Will Suit

This role suits engineers who like a mix of autonomy and collaboration, and who are comfortable working in an environment that’s still evolving.

We’re a distributed team with a growing engineering presence in India, so comfort with async collaboration and clear written communication is important.

We use agentic coding tools heavily (e.g., Cursor and Claude Code) to plan, scaffold, refactor, and debug production code, while maintaining strong engineering judgment and ownership of outcomes.

Interview Process

Our process is designed to be practical and respectful.

1. CV & Profile Review – Relevant experience and background
2. Initial Chat (30 mins) – Motivation and role fit
3. Technical Interview (60 mins) – Architecture, design choices, and real scenarios
4. Practical Exercise + Discussion (60 mins) – A small task related to the role

What We Offer

• Competitive salary with meaningful equity
• Fully remote, async-friendly working
• Supportive, low-ego engineering culture
• Budget for learning and professional development

If you’re interested in building and improving real systems in a growing product company, we’d love to hear from you.