Autoplay.ai is a fast-growing US startup that automatically turns user session replays and analytics events into clear, AI-powered insights (user intent, friction points, summaries, highlights). We’re currently scaling the team and actively looking for a Senior Data Engineer(Poland, remote)💰 Salary: 27 000-36 000 PLN/month🌎 Fully remote🕦 Full-time position☑️ B2BWhat you’ll be working on:Data Pipeline Architecture & Management Design, orchestrate, and maintain our multi-source data pipeline (RRWeb events, analytics events, video frames, metadata). Manage and optimize Airflow DAGs (scheduling, retries, dependency management, error handling, backfilling). Integrate and scale Airbyte connectors to pull data from tools like PostHog, Mixpanel, Pendo, and custom APIs.

Build high-reliability pipelines that can handle large, bursty session replay data.

Pipeline Reliability & Observability Implement end-to-end monitoring: logs, metrics, alerts, data quality checks, schema validations. Reduce pipeline failures and rate-limit issues (e.g., PostHog ingestion constraints). Introduce automatic retries, dead-letter queues, and backpressure strategies. Backend Engineering Build and optimize backend services (Python/FastAPI, Node, etc.) that consume and expose pipeline outputs. Improve the performance of data storage (Postgres/Neon, vector DBs, GCS). Implement caching layers for metadata, summaries, and user-level insights. Scalability & Performance

Architect systems that can scale across:

High-volume session replays Large embeddings JSON augmentation workloads Batch and real-time computation

Identify bottlenecks and implement optimizations across the pipeline (I/O, compute, caching, parallelization). Ownership of the Full Augmentation Flow Directly manage all backend systems that produce:

Augmented interactions Markdown summaries Session highlights User intent & frictions Session tags One-liner summaries Product sections User flow GCS output storage

What you need to have: 5+ years in data engineering or backend engineering Deep experience with Apache Airflow, DAG design, and orchestration at scale Strong familiarity with Airbyte, ETL/ELT patterns, and connector configuration Strong Python engineering background (FastAPI / Django / async patterns) Experience processing large JSON datasets or high-volume event streams Proven track record of building scalable, cost-efficient, well-monitored data systems Familiarity with GCP (GCS, Cloud Run, Pub/Sub), AWS, or similar cloud environments It’s a big plus if you have: Experience with RRWeb or session replay data Background in AI/ML data pipelines Experience with vector databases, embeddings, or semantic search Understanding of clickstream analytics DevOps exposure (Docker, Terraform, CI/CD) What we offer: Fully remote A friendly work atmosphere Growing the company together - your opinion counts Building modern solutions that have a real, measurable impact on our clients’ businesses Additional benefits tailored to your needs The entire recruitment process will be fully remote and will consist of several stages, such as a conversation with the recruiter, a technical interview that includes a live-coding part, and meetings with team members and managers. These will allow us to get to know you better, but they will also give you the opportunity to get to know the company, so that both sides can be sure we’re making the right choice.