Member of Technical Staff 3 (Data Engineering)

Nielsen is seeking a Member of Technical Staff 3 (MTS3) Data Engineer to lead the architectural design and build of our next-generation global data platform. In this role, you will architect, scale, and maintain high-throughput pipelines that capture and analyze complex audience consumption patterns across OTT, linear TV, radio, and social media worldwide. As an MTS3, you will drive operational excellence, system availability, and high-performance engineering practices. Beyond execution, you will foster a culture of technical innovation, drive architectural standards, and mentor mid-level and junior engineers across the organization.

Responsibilities:

Architecture and System Design: Collaborate with business stakeholders, data scientists, and product managers to define technical roadmaps, platform architecture, and system requirements.

Pipeline and Platform Engineering: Design, build, test, and deploy resilient, scalable batch and real-time data pipelines (ETL/ELT) processing multi-terabyte datasets.

Cloud Migration and Modernization: Lead technical execution for migrating legacy solutions to AWS cloud-native architectures, ensuring cost optimization, high availability, and disaster recovery.

Code Quality and Operational Excellence: Conduct rigorous code reviews, establish engineering best practices, enforce strict CI/CD guidelines, and troubleshoot complex production incidents.

Technical Leadership and Mentorship: Guide, pair-program with, and mentor junior and mid-level software/data developers, fostering an environment of continuous learning and technical curiosity.

Requirements:

Experience: 6+ years of hands-on data engineering experience, with demonstrated ownership of complex, distributed systems.

Core Languages: Advanced proficiency in Python and PySpark (or Scala).

Distributed Computing and Data Processing: Deep expertise in Apache Spark, Pandas, and optimizing distributed data processing workloads.

Cloud Platforms: Hands-on expertise with cloud infrastructure (AWS preferred: S3, EMR, Redshift, Glue, IAM, Lambda).

Workflow and Orchestration: Proven experience building and managing scalable data pipelines using Apache Airflow.

DevOps and Infrastructure: Strong Linux/Unix administration skills, working knowledge of Docker and Kubernetes, and hands-on experience building CI/CD pipelines (GitLab CI/CD).

Communication: Excellent verbal and written English communication skills; comfortable presenting technical decisions to non-technical stakeholders.

Preferred / Nice-to-Have Qualifications:

Hands-on experience developing AWS-native serverless or microservices-based data architectures.

Experience operating within Agile/Scrum delivery frameworks.

Familiarity with streaming/messaging architectures (e. g., Apache Kafka, AWS Kinesis).

Background in media, ad-tech, or large-scale audience analytics systems.

Technology Stack:

Data and Compute: Apache Spark, Apache Airflow, Pandas, Python.

Cloud and Infra: AWS (EMR, S3, Glue, Redshift), Docker, Kubernetes, Linux/Bash.

CI/CD and Tools: GitLab CI/CD, Git, Jira, Confluence.