NerdWallet is on a mission to bring clarity to all of life’s financial decisions, and they are seeking a Staff Data Engineer to lead the design and maintenance of business-critical data assets. The role involves tackling complex data challenges and collaborating with cross-functional teams to ensure data systems align with strategic goals.
Responsibilities:
- Lead the design, development, and maintenance of business-critical data assets, ensuring they are accurate, reliable, and aligned with evolving business priorities
- Drive technical innovation and process excellence, evaluating emerging technologies and implementing scalable, efficient solutions that improve data pipeline performance and reliability
- Tackle complex technical challenges - balancing scalability, security, and performance - while providing clear rationale for architectural decisions and aligning outcomes across teams
- Ensure data pipeline reliability and observability, proactively identifying and resolving issues, investigating anomalies, and improving monitoring to safeguard data integrity
- Build trust and alignment across cross-functional teams through transparent communication, collaborative problem-solving, and a deep understanding of partner needs
- Bring clarity and direction to ambiguity, taking ownership of initiatives that span multiple domains or teams, and providing technical leadership to ensure successful delivery
- Prioritize work strategically, balancing business impact, risk, and execution to drive measurable outcomes that support organizational goals
- Act as a trusted technical advisor and thought leader, shaping the team’s long-term architecture and influencing best practices
- Foster a culture of technical excellence and continuous learning, mentoring engineers and championing modern data engineering practices, including AI and automation-enabled solutions
Requirements:
- 7+ years of relevant professional experience in data engineering
- 5+ years of experience with AWS, Snowflake, DBT, Airflow
- Advanced level of proficiency in Python and SQL
- Working knowledge of relational databases and query performance tuning (SQL)
- Working knowledge of streaming technologies such as Storm, Kafka, Kinesis, and Flume
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent professional experience)
- Advanced level of proficiency applying principles of logical thinking to define problems, collect data, establish facts, and draw valid conclusions
- Experience designing, building, and operating robust data systems with reliable monitoring and logging practices
- Strong communication skills, both written and verbal, with the ability to articulate information to team members of all levels and various amounts of applicable knowledge throughout the organization