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Global brand and Bangalore metro boost applicant pool, but senior, niche data-engineering leadership reduces generic competition.
Strong data-engineering focus is broadly transferable, though media measurement domain experience is advantageous.
Mandatory 12+ years and specific Java/Spring Big Data and AWS skills enforce strict candidate filters.
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Lead Data Engineering teams within the Digital & AI organization to develop and scale high-volume data pipelines and measurement solutions.
Own the end-to-end data lifecycle including ingestion, processing, validation, and reporting to ensure data accuracy and platform reliability.
Drive technical roadmap, prioritize resources, and collaborate with Product Management and Data Science for automated panel data processing systems.
Minimum 12 years of relevant experience in data engineering and backend development.
Strong proficiency in Java and Spring Boot with hands-on experience in Big Data technologies such as ClickHouse, OpenSearch, Spark, and ETL tools like Logstash.
Advanced knowledge of AWS cloud services (Lambda, S3, EC2) and monitoring tools like Grafana.
Work Experience Required: 12+ years relevant experience
Experienced leader in managing engineering teams within Agile environments, focused on roadmap planning and stakeholder communication.
Proven ability in building and scaling complex data pipelines with strong emphasis on data validation, ETL optimization, and performance standards.
Domain experience or familiarity with digital measurement, panel management, streaming data collection, or attribution ecosystems preferred but not mandatory.