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4 weeks ago
We are seeking a Senior Data Engineer to design and implement the backbone of our data infrastructure for a large-scale Television Audience Measurement (TAM) platform.
About the RoleThis role is central to building efficient, reliable, and scalable pipelines that move, transform, and manage data collected from thousands of edge devices and processed through our backend systems.
Key Responsibilities:- Design, develop, and maintain data pipelines for ingesting, validating, and transforming telemetry and audio signature data.
- Work with tools like Kafka, Airflow, rsync, PostgreSQL, and MongoDB to orchestrate and manage data flow.
- Collaborate with the TAM box collection system and headend systems to ensure seamless ingestion.
- Implement efficient batch data workflows for daily audience analytics, panel metrics, and report generation.
- Develop modular data processing scripts and transformations in Python and Bash.
- Ensure high reliability, correctness, and fault tolerance in all data movement processes.
- Implement logging, retry logic, and monitoring to track pipeline health and data anomalies.
- Support data scientists by preparing clean, structured datasets and integrating model outputs into downstream systems.
- 6+ years of experience in data engineering, backend development, or similar fields.
- Strong proficiency with ETL pipelines, time-series data, and batch processing systems.
- Advanced skills in Python and Bash for scripting and automation.
- Experience with Kafka, Airflow, PostgreSQL, and MongoDB (or similar alternatives).
- Solid understanding of data structures, data integrity, schema management, and storage optimization.
- Comfortable working in Linux environments with on-prem infrastructure and physical servers.
- Experience writing and optimizing SQL queries, views, and stored procedures.
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