Engineering Manager

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it's consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

We are building the future of media measurement, and our modern data platform is at the heart of this

transformation. We are seeking an experienced Manager, Data Engineering to lead a new, high-impact

team dedicated to designing, building, and scaling our next-generation data processing platform and

robust ETL/ELT pipelines.

This is a critical leadership role for a strong technical problem-solver. You will guide a talented team of

Data and Platform Engineers responsible for designing, building, and scaling the foundational data

infrastructure, tools, and pipelines that process petabytes of audience data.

This position requires a leader who can bridge the gap between massive data volumes, complex business

logic, and reliable, highly-available systems. You'll be the key technical and people leader, driving project

execution from concept to production and solving complex architectural challenges that are fundamental

to how we measure audience engagement and deliver critical client insights.

What You'll Do

● Lead & Mentor: Manage, coach, and develop a high-performing team of Data and Platform

Engineers, fostering a culture of innovation, collaboration, and engineering excellence focused

on data quality and throughput.

● Platform Delivery: Oversee the end-to-end software development lifecycle (SDLC) for our core

data pipelines and data warehouse—from concept and architecture to deployment,

observability, and iteration.

● Technical Strategy: Partner with product managers, architects, and data consumers to define the

technical roadmap and architecture for a scalable, reliable, and secure data processing platform.

● Problem-Solving: Act as the primary technical problem-solver for the team, guiding them

through complex system design, data integration challenges, and performance bottlenecks in big

data environments.

● Cross-Functional Collaboration: Serve as the key interface between your engineering team and

stakeholders in product, operations, and other business units to translate complex data needs

into concrete technical solutions.

● Engineering Excellence: Champion and enforce engineering best practices for code quality,

automated testing, CI/CD, security, and platform reliability across all data infrastructure.

● Hands-On Guidance: Provide technical guidance on designing, implementing, and optimizing

large-scale ETL/ELT processes, real-time data streaming solutions, and big data stores.

● 8+ years of hands-on Data Engineering or Software Engineering experience focused on large-scale data processing.

● 1-3+ years of experience in an engineering leadership or management role, with a proven track record of building and managing high-performing technical teams.

● Strong Big Data Expertise: Deep experience building and scaling cloud-native data platforms and distributed systems (e.g., using AWS).

● Core Programming Skills: Proficiency in high-volume data processing using Spark, Scala, and/or Python.

● Data Pipeline Mastery: Extensive experience with Data ETL/ELT pipeline design, data warehousing concepts, and data modeling for scalability and efficiency.

● Database Knowledge: Proficiency in designing and managing RDBMS (e.g., MySQL), including query optimization, and hands-on experience with NoSQL databases (e.g., MongoDB, DynamoDB).

● Streaming Experience: Working knowledge of real-time streaming data processing using technologies like Kafka or similar.

● DevOps & Infrastructure: Familiarity with DevOps techniques, CI/CD pipelines, Infrastructure as Code (e.g., Terraform), and containerization (e.g., Docker/Kubernetes).

● Operational Excellence: Experience with instrumenting logging, monitoring, and observability into data applications.

● Exceptional Problem-Solver: A demonstrated ability to navigate ambiguity, break down complex technical problems into actionable plans, and lead a team to a solution.

● Excellent Communication: The ability to effectively communicate complex technical concepts to both technical and non-technical audiences, driving alignment across teams.

● Domain Bonus: Experience in the media, ad-tech, or audience measurement industry is a strong plus.

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