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Tier-1 brand, metro location, mid-level generalist data role with broad skill requirements increases competition.
Strong transferable data-engineering skills but adtech-specific forecasting and measurement increase domain sensitivity.
Explicit 5–8 years plus mandatory big-data, streaming, and Databricks expertise raises shortlisting strictness.
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Design and develop scalable high-volume data pipelines and backend services supporting advertising analytics, forecasting, and reach reporting.
Collaborate with product teams to translate reporting requirements into reliable, performant batch and real-time data processing systems using modern big data tools (e.g., Spark, Flink, Kafka, Airflow).
Drive data modeling best practices, ensure data quality and system reliability, mentor junior engineers, and support 24x7 platform operations.
Bachelor’s degree in computer science or related field.
5-8 years of software engineering experience focusing on data-intensive systems.
Expertise with distributed data processing frameworks such as AWS Kinesis and Flink; proficiency in at least two programming languages (Java, Python, Go).
Experience building and managing large-scale streaming or batch processing platforms; familiarity with cloud services (especially AWS), microservices, containerization, and CI/CD pipelines.
Experienced in building and optimizing large-scale reporting and forecasting data systems within adtech or similar domains.
Strong capability in both batch and real-time data pipeline architectures with proven operational excellence.
Effective mentor and technical leader capable of shaping engineering practices and supporting cross-functional collaboration.