Senior Engineering Manager - Data Engineering

Responsibilities

• Leadership & Strategy
• Lead and mentor high-performing engineering teams, fostering a culture of technical excellence, automation, and continuous improvement.
• Own the Tech Roadmap and long-term planning for data engineering workstreams, ensuring alignment with product goals and business efficiency initiatives.
• Partner closely with Product Management (Head of Streaming+ Infrastructure) and Data Science to define system requirements for automated panel data processing and eligibility.
• Manage resource bandwidth and prioritize quarterly planning integrity over ad-hoc requests to ensure project delivery.
• Technical Execution
• Oversee the architecture and scaling of data pipelines using technologies like Spring Boot, ClickHouse, OpenSearch, and Logstash.
• Drive the transition toward automated, longitudinal data processing to replace deterministic manual processes.
• Ensure robust data validation across complex event streams, batch jobs, and downstream reporting dashboards.
• Implement rigorous performance standards and "tech excellence" line items, such as Cloud Cost Optimization and SEV-1 Reduction targets.
• Resolve critical technical blockers related to data schemas, device-process date misalignment, and international market integrations.
• Implement and oversee ETL job monitoring and performance optimization for critical data pipelines.
• Technical Proficiency
• Backend & Frameworks: Deep expertise in Java and Spring Boot.
• 12+years of relevant experience.
• Data Systems: Hands-on experience with Big Data technologies (ClickHouse, ElasticSearch/OpenSearch, Spark, MDL) and ETL tools (Logstash).
• Cloud Ecosystems: Advanced knowledge of AWS services, including Lambda, S3, and EC2, along with Grafana for monitoring and observability.
• Data Validation: Strong SQL skills and experience validating large-volume, high-variability datasets and event pipelines.
• Data Pipeline Management: Strong experience with ETL job monitoring, optimization, and building/scaling high-volume data pipelines.
• Leadership Capabilities
• Proven experience managing engineering teams in an Agile environment with a focus on roadmap visibility and stakeholder communication.
• Ability to conduct rigorous performance calibration and talent assessment to maintain a high-quality engineering bar.
• Strong experience in cross-functional collaboration across Product, Data Science, and Operations teams.
• Nice-to-Have Skills
• Experience in digital measurement, panel management, or attribution ecosystems.
• Knowledge of Connected TV (CTV) platforms and streaming data collection.
• Familiarity with privacy-compliant, software-first measurement solutions.
• Handson of Databricks.

Additional Information

Nielsen is seeking a technical and strategic Senior Engineering Manager to lead our Data Engineering teams within the Digital & AI organization. This role is critical for driving the development of high-scale data pipelines and measurement solutions, including our Streaming+ Infrastructure and the Panelist Intelligence Engine (PIE). The ideal candidate will oversee the end-to-end data lifecycle-from ingestion and processing to validation and reporting-ensuring the highest standards of data accuracy and platform integrity for our global digital measurement products.

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