Data Engineer Lead

We are hiring a Tech Lead / SDE IV to anchor and grow our Data Engineering capability within our Demand-Side Platform (DSP). This is a high-impact, technically hands-on leadership role at the intersection of real-time data infrastructure, programmatic advertising, and scalable backend systems.

Requirements:

• 8+ years of software engineering experience, with at least 4 years focused on data engineering or large-scale data systems.
• Prior experience in ad-tech, programmatic advertising, or real-time bidding (RTB) environments strongly preferred.
• Experience in ML engineering, feature engineering, building offline training pipelines, or collaborating closely on model productionisation is preferred.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

Data Engineering (Core):

• Deep expertise in distributed stream processing frameworks: Apache Kafka, Apache Flink, or Apache Spark Structured Streaming.
• Strong command of SQL and experience optimising complex analytical queries at petabyte scale.
• Hands-on experience with real-time analytical databases, particularly StarRocks; familiarity with Snowflake or ClickHouse is a plus.
• Proficiency with workflow orchestration tools: Apache Airflow, Prefect, or Dagster.
• Solid understanding of data modelling, dimensional modelling, OBT patterns, and event-driven schemas relevant to ad impression and attribution data.
• Familiarity with open table formats: Apache Iceberg, Delta Lake, or Apache Hudi.

Backend and Systems:

• Proficiency in Python (primary) and/or Java/Scala for building production-grade services and data processing jobs.
• Experience designing and building RESTful APIs and/or gRPC-based microservices.
• Working knowledge of low-latency data stores (Aerospike, Cassandra) used for real-time lookups in the bidding path.
• Comfortable with containerised deployments on Kubernetes and CI/CD pipelines (GitHub Actions, ArgoCD, or similar).

Ad-Tech Domain Knowledge:

• Understanding of the RTB ecosystem: DSPs, SSPs, ad exchanges, bid request/response lifecycle, and OpenRTB protocol.
• Familiarity with identity resolution approaches: cookie IDs, device IDs, UID2 / RampID, and privacy-preserving identity.
• Exposure to audience segmentation, frequency capping, pacing algorithms, or attribution models is a significant plus.
• Awareness of privacy regulations (GDPR, CCPA) and their implications for data pipelines and user-level data handling.

Leadership and Collaboration:

• Demonstrated experience leading technical squads or functioning as a technical anchor on cross-functional projects.
• Strong written and verbal communication skills; ability to translate technical complexity for non-engineering stakeholders.
• Track record of driving projects from ambiguous requirements to production with high engineering quality.