Data Engineer II

At NerdWallet, we’re on a mission to bring clarity to all of life’s financial decisions​ and every great mission needs a team of exceptional Nerds. We’ve built an inclusive, flexible, and candid culture where you’re empowered to grow, take risks, and be unapologetically yourself (cape optional). Whether remote or in-office, we support how you thrive best. We invest in your well-being, development, and ability to make an impact​ because when one Nerd levels up, we all do.

Data engineers are the builders behind the insights that drive smarter decisions. They design and scale reliable data pipelines and models that power analytics, experimentation, and strategic decision-making across the company. As a Data Engineer II, you’ll tackle complex, data challenges - partnering closely with your Data Org members. You’ll combine technical expertise with clear communication and thoughtful collaboration to ensure our data systems are not only technically sound, but also deeply aligned with NerdWallet’s strategic goals.

You’ll work directly within a product vertical - shaping the data that drives business decisions, product innovation, and user experiences. This is a unique opportunity to see your work translate into real-world outcomes, accelerating NerdWallet’s mission through data that’s closer than ever to the business.

You’ll design, develop, and maintain data systems and pipelines that serve as the foundation for analytics and product innovation in a fast-paced, ever-evolving environment. The right candidate is comfortable adapting to shifting priorities.

This role sits within Data Org and reports to a Senior Manager of Data Engineering. You’ll join a passionate team of Nerds who believe clean, scalable data is at the heart of helping consumers make smarter financial decisions.

Where you can make an impact:

• Lead well-scoped data assets - accurate, reliable, documented, aligned to stakeholder needs.
• Build and improve pipelines using established patterns, focused on maintainability, scalability and quality.
• Solve moderately complex problems independently; escalate when tradeoffs or dependencies call for broader input.
• Strengthen pipeline reliability and observability - monitor jobs, investigate failures, improve tests, prevent recurrence.
• Communicate clearly with cross-functional partners on requirements, assumptions and progress.
• Break down ambiguous work, ask thoughtful questions and partner with senior engineers on the path forward.
• Prioritize by impact, urgency, risk - communicate tradeoffs as scope or timing shifts.
• Apply sound judgment on implementation; seek feedback to sharpen design and execution.
• Write clean, tested, documented code; adopt modern practices, including AI-enabled tooling.
• Grow technical depth over time - take on harder workstreams, learn from feedback, reviews and mentorship.

Your experience:

• 3+ years in data engineering, analytics engineering, software engineering, or related.
• Hands-on with modern data stack tools: AWS, Snowflake, dbt, Airflow, Databricks, or similar.
• Strong SQL; working proficiency in Python for pipeline development, transformation, automation, debugging.
• Comfortable with AI-assisted tools like Cursor or GitHub Copilot.
• Working knowledge of relational databases, data modeling, query performance.
• Experience building and troubleshooting pipelines in production.
• Familiarity with data quality, monitoring, logging, testing, observability.
• Logical problem-solving - define issues, investigate anomalies, draw sound conclusions.
• Comfortable within established patterns, alert to opportunities to improve them.
• Strong written and verbal communication, clear across engineering, analyst, and business audiences.
• Bachelor's or Master's in Computer Science, Engineering, related field, or equivalent experience.