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Strong employer brand, popular data-engineer role, metro hiring and broad skill requirements increase competition.
Requires specialized data platform, lakehouse and adtech experience, so background transferability across industries is limited.
Explicit 8+ years requirement plus specific lakehouse, streaming, and cloud tech mandates high shortlisting strictness.
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Design and maintain high-scale ingestion, ETL, and activation data pipelines processing billions of ad events daily in cloud native environments.
Modernize legacy ad-tech systems into open lakehouse architectures (Iceberg, Delta, Hudi) embedding observability, data lineage, and automation frameworks.
Provide architectural leadership and mentorship, acting as a domain expert in distributed streaming big data systems and collaborating cross-functionally with data science and engineering teams.
8+ years of experience designing and operating enterprise-scale data platforms with high-throughput pipelines.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or related field.
Hands-on expertise with AWS/GCP/Azure, open table formats (Iceberg, Delta, Hudi), distributed compute frameworks (Spark, Flink, Presto), and streaming platforms (Kafka, Kinesis, Pub/Sub).
Familiarity with advertising workflows including forecasting, yield optimization, identity, and campaign execution.
Experienced in modern cloud-native data engineering with a focus on scalable, low-latency real-time and batch processing systems in ad-tech environments.
Strong architectural mindset with ability to lead platform modernization and embed operational excellence practices including CI/CD and observability.
Skilled collaborator able to partner with data science and product teams and mentor junior engineers globally.