Principal Data Engineer (MTS4)

Nielsen; United States; Remote; USD 90,000 - 160,000; Full time

Job summary

An established industry player is seeking a Principal Data Engineer to lead the strategy and execution of large-scale data solutions. In this pivotal role, you will tackle complex challenges, collaborate with cross-functional teams, and shape the data roadmap that influences the organization’s technical direction. Your expertise in designing robust data pipelines using cutting-edge technologies will drive operational excellence and innovation. This dynamic position offers the opportunity to mentor engineering talent and elevate data capabilities across multiple teams. If you are passionate about making a significant impact in the media landscape, this role is perfect for you.

Qualifications

• 6+ years of software/data engineering experience with large-scale systems.
• Proficiency in Spark, Airflow, Kafka, and major programming languages.

Responsibilities

• Architect and define the scope of critical data pipelines and platforms.
• Lead design reviews and champion best practices for coding and data quality.

Skills

Data Engineering

Problem-Solving

Cross-Functional Collaboration

Technical Leadership

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Spark

Airflow

Kafka

Hadoop

Flink

Kubernetes

Snowflake

Job description

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.

As a Principal Data Engineer (MTS 4), you will drive the strategy, architecture, and execution of large-scale data solutions across our function. This role involves tackling highly ambiguous, complex challenges where the business problem may not be fully defined at the outset. You will partner closely with cross-functional teams (Engineering, Product, Operations) to shape and deliver our data roadmap. Your work will have a profound impact on the company’s data capabilities, influencing multiple teams’ technical and product direction.

You should bring deep expertise in designing and developing robust data pipelines and platforms, leveraging technologies such as Spark, Airflow, Kafka, and other emerging tools. You will set standards and best practices that raise the bar for engineering excellence across the organization.

Key Responsibilities

• Architect & Define Scope
  Own end-to-end design of critical data pipelines and platforms in an environment characterized by high ambiguity.
  Translate loosely defined business objectives into a clear technical plan, breaking down complex problems into achievable milestones.
• Technology Leadership & Influence
  Provide thought leadership in data engineering, driving the adoption of Spark, Airflow, Kafka, and other relevant technologies (e.g., Hadoop, Flink, Kubernetes, Snowflake, etc.).
  Lead design reviews and champion best practices for coding, system architecture, data quality, and reliability.
  Influence senior stakeholders (Engineers, EMs, Product Managers) on technology decisions and roadmap priorities.
• Execution & Delivery
  Spearhead strategic, multi-team projects that advance the organization’s data infrastructure and capabilities.
  Deconstruct complex architectures into simpler components that can be executed by various teams in parallel.
  Drive operational excellence, owning escalations and ensuring high availability, scalability, and cost-effectiveness of our data solutions.
  Mentor and develop engineering talent, fostering a culture of collaboration and continuous learning.
• Impact & Technical Complexity
  Shape how the organization operates by introducing innovative data solutions and strategic technical direction.
  Solve endemic, highly complex data engineering problems with robust, scalable, and cost-optimized solutions.
  Continuously balance short-term business needs with long-term architectural vision.
• Process Improvement & Best Practices
  Set and enforce engineering standards that elevate quality and productivity across multiple teams.
  Lead by example in code reviews, automation, CI/CD practices, and documentation.
  Champion a culture of continuous improvement, driving adoption of new tools and methodologies to keep our data ecosystem cutting-edge.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
• 6+ years of software/data engineering experience, with significant exposure to large-scale distributed systems.
• Technical Expertise:
  Demonstrated proficiency with Spark, Airflow, Kafka, and at least one major programming language (e.g., Python, Scala, Java).
  Experience with data ecosystem technologies such as Hadoop, Flink, Snowflake, Kubernetes, etc.
  Proven track record architecting and delivering highly scalable data infrastructure solutions.
• Leadership & Communication:
  Ability to navigate and bring clarity in ambiguous situations.
  Strong cross-functional collaboration skills, influencing both technical and non-technical stakeholders.
  Experience coaching and mentoring senior engineers.
• Problem-Solving:
  History of tackling complex, ambiguous data challenges and delivering tangible results.
  Comfort making informed trade-offs between opportunity vs. architectural complexity.