We are seeking a highly skilled **Principal Software Engineer – Data Engineering** to design, develop, and optimize scalable data platforms and pipelines. The ideal candidate will have strong expertise in **Python, SQL, Snowflake (or equivalent cloud data warehouse), cloud technologies, CI/CD practices, and AI-enabled data solutions**. This role requires technical leadership, architecture ownership, mentoring capabilities, and hands-on engineering excellence.
Key Responsibilities
Data Engineering & Platform Development
- Design and implement scalable, reliable, and secure data pipelines.
- Develop ETL/ELT solutions for processing large-scale structured and unstructured datasets.
- Build data ingestion frameworks supporting batch and near real-time processing.
- Design and optimize data models for analytics, reporting, and machine learning workloads.
- Ensure high data quality, governance, observability, and reliability across data platforms.
Cloud & Data Warehouse
- Architect and maintain cloud-native data solutions on AWS or Azure or GCP.
- Develop and optimize solutions using **Snowflake** or equivalent cloud data warehouse technologies.
- Implement data lake and lakehouse architectures.
- Optimize storage costs, compute utilization, and query performance.
Software Engineering Excellence
- Develop production-grade applications and frameworks using Python.
- Perform code reviews and establish engineering best practices.
- Drive architectural decisions and technology selection.
- Ensure adherence to security, scalability, and reliability standards.
CI/CD & DevOps
- Design and implement CI/CD pipelines for data and application deployments.
- Automate build, test, deployment, and monitoring processes.
- Manage Infrastructure as Code (IaC) using Terraform, CloudFormation, or similar tools.
- Improve deployment reliability and observability.
AI & Advanced Analytics
- Enable AI/ML workflows by building robust feature and training data pipelines.
- Work with AI teams to operationalize machine learning models.
- Explore Generative AI, LLM integrations, vector databases, and AI-driven automation solutions.
- Support model monitoring, governance, and deployment pipelines.
Leadership & Mentoring
- Provide technical leadership across multiple engineering teams.
- Mentor senior engineers and establish engineering standards.
- Collaborate with architects, product managers, and business stakeholders.
- Drive innovation and strategic technology initiatives.
Qualifications
10+ years of experience in Data Engineering.
- Strong expertise in **Python programming**.
- Advanced SQL development and performance tuning skills.
- Experience with **Snowflake** or equivalent cloud data warehouse technologies.
- Strong understanding of data modeling, ETL/ELT frameworks, and data governance.
- Experience with cloud platforms:
- Microsoft Azure (Preferred)
- AWS
- Google Cloud Platform
DevOps & CI/CD
- Experience with: Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, Knowledge of Docker and Kubernetes., Infrastructure as Code experience.
AI & Modern Data Technologies
Exposure to:
- Machine Learning pipelines
- Generative AI concepts
- LLM integrations
- Vector databases
- RAG architectures
- Prompt engineering basics
Preferred Qualifications:
- Experience building enterprise-scale data platforms.
- Knowledge of Spark, Databricks, Kafka, or streaming technologies.
- Understanding of Data Mesh and modern data architecture principles.
- Experience in observability and monitoring tools.
- Snowflake, Azure, AWS, or GCP certifications are a plus.
Desired Competencies
- Technical leadership
- Solution architecture
- Strategic thinking
- Stakeholder management
- Problem-solving
- Mentoring and coaching
- Strong communication skills
- Agile development practices
Success Metrics
- Reliable and scalable data platform delivery.
- Reduced pipeline failures and improved SLA compliance.
- Improved data quality and governance.
- Faster deployment cycles through CI/CD automation.
- Successful adoption of AI-enabled data solutions.
- Increased engineering productivity and platform efficiency.
Our Benefits
- Flexible working environment
- Volunteer time off
- LinkedIn Learning
- Employee-Assistance-Program (EAP)
NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/
About NIQ
NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.
For more information, visit NIQ.com
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Our commitment to Diversity, Equity, and Inclusion
At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion
Skills Required
- 10+ years of experience in Data Engineering
- Strong expertise in Python programming
- Advanced SQL development and performance tuning
- Experience with Snowflake or equivalent cloud data warehouse
- Experience with AWS cloud platform
- Experience with Google Cloud Platform
- Experience with Microsoft Azure (Preferred)
- Experience with data modeling, ETL/ELT frameworks, and data governance
- Design and implement scalable, reliable data pipelines for large structured and unstructured datasets
- Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD)
- Knowledge of Docker and Kubernetes
- Infrastructure as Code experience (Terraform, CloudFormation)
- Experience building production-grade applications and conducting code reviews
- Exposure to machine learning pipelines, Generative AI, LLM integrations, vector databases, RAG, prompt engineering
- Experience with Spark, Databricks, Kafka or streaming technologies
- Experience in observability and monitoring tools
- Snowflake, Azure, AWS, or GCP certifications (plus)
NielsenIQ Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NielsenIQ and has not been reviewed or approved by NielsenIQ.
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Parental & Family Support — Public materials highlight paid parental leave in the U.S., with additional paid disability time for birth parents. Parental leave is positioned as a standout element of the package.
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Leave & Time Off Breadth — Unlimited or flexible PTO is referenced alongside paid holidays and sick leave, providing broad time-off options in many roles. Actual use can vary by team norms, but the formal breadth is notable.
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Flexible Benefits — Work-from-home and hybrid arrangements are supported in many roles, with remote-friendly practices described across business lines. Flexibility is frequently positioned as a meaningful advantage.
NielsenIQ Insights
What We Do
NielsenIQ is the industry leader in global measurement and data analytics, and the most trusted source for retail and consumer intelligence. We deliver the complete truth to retailers, manufacturers, and our partners through our comprehensive data sets and powerful insights. We enable businesses to make critical decisions confidently, accelerating growth and optimizing performance.
Why Work With Us
We empower companies around the world to make bold decisions and transform their business with trusted data, solutions, and insights. Joining NielsenIQ means experiencing countless learning opportunities and gaining numerous pathways for growth.
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