Data Engineer

Our client is a leader in AI-powered performance marketing, operating across 25+ verticals with unmatched precision, speed, and scale. Their proprietary technology stack integrates seamlessly with major media platforms, enabling real-time event-level data exchange, optimization, and attribution.
At the core of their operation is a deep commitment to AI-driven decision-making. From real-time bidding engines and predictive lead scoring to campaign automation and anomaly detection, their in-house AI models are central to how we scale campaigns, reduce inefficiencies, and outperform market benchmarks.
They’ve built and continue to evolve a robust internal platform to empower media buyers, analysts, and operators with real-time alerts, smart recommendations, and semi-autonomous optimization tools.

Role Summary
‍Builds high-performance, reliable data systems, including real-time pipelines, tracking, and Feature Store foundations — enabling both analytics and ML production.

Required skills:

• Strong software engineering fundamentals (clean code, testing, system design)
• Proven experience building real-time, low-latency data services
• Experience operating in production at scale (high throughput, distributed systems)
• Strong background with modern data stack (e.g., Kafka/Kinesis, Spark/Flink/Beam, Snowflake/BigQuery/Redshift)
• Ability to design schemas, ingestion flows, and data quality frameworks

• Experience collaborating with ML teams on feature availability and consistency

   

Preferred Qualifications (Nice to Have)

• Experience supporting ML systems (feature serving, online/offline consistency)
• Production experience with model inference pipelines
• Strong DevOps experience (Docker, Kubernetes, CI/CD)
• Experience with cloud-native architectures (AWS/GCP)
• Experience implementing data observability / lineage frameworks