Senior Data Engineer

Resonate is a leading provider of high-quality, AI-powered consumer data, intelligence, and technology, empowering marketers to create a more personalized world that increases customer acquisition and lifetime value. Our SaaS platform, Ignite, and our Data-as-a-Service (DaaS) offerings provide unparalleled insights into consumer motivations, values, and behaviors, enabling our clients to connect with their target audiences in more meaningful and effective ways. We are a dynamic and fast-growing company seeking passionate and innovative individuals to join our team!

We’re looking for a Senior Data Engineer who combines deep technical expertise with strong communication skills and a proactive mindset. You’ll design, build, and optimize complex data pipelines in a cost-conscious environment while actively collaborating with your squad. This role is ideal for engineers who love sharing their work, navigating ambiguity, and understand that “it runs” is not the same as “it runs efficiently.” Thriving here means taking ownership, balancing innovation with operational excellence, and proactively seeking out opportunities for optimization.

Key Responsibilities

• Design and develop high-performance data pipelines using Scala/Spark on AWS EMR.

• Build new features and data products while maintaining operational excellence.

• Optimize pipelines for both performance and cost efficiency.

• Debug complex distributed system issues using appropriate tools and methodologies.

• Implement comprehensive monitoring and observability from day one.

• Write efficient Snowflake/Snowpark procedures across multiple languages.

• Balance new development with continuous improvement of existing systems.

Qualifications & Experience Requirements

• Technical Requirements:

  • 5+ years of hands-on experience with Apache Spark using Scala exclusively (no PySpark).

  • Proven track record of optimizing large-scale data pipelines for performance and cost.

  • Strong AWS EMR experience, including fleet management and instance optimization.

  • Proficiency in AWS Step Functions.

  • Deep understanding of distributed computing principles and resource management.

  • Experience debugging and tuning multi-terabyte daily workloads.

  • Comfort working across Scala, Python, and SQL as needed.

  • Experience with probabilistic data structures for high-cardinality data processing.

• Critical Skills:

  • Advanced troubleshooting abilities in distributed systems.

  • Strong understanding of data skew mitigation strategies.

  • Metrics-first mindset—measuring before and after optimization.

  • Root cause analysis expertise, preventing issues rather than just fixing them.

• Mindset Requirements:

  • Cost-conscious, treating company money like your own.

  • Balance between innovation and operational excellence.

  • Proactive in optimization—seeing inefficiencies as opportunities.

  • Communicate early and often, especially around risks and blockers.

  • Ability to interpret needs beyond stated requirements.

Preferred Qualifications

• Experience designing large-scale, observable, and maintainable systems.

• Proven ability to balance building new capabilities with perfecting existing systems.

• Strong track record of mentoring and knowledge sharing.

• Background in cost/performance tradeoff decision-making.

• Passion for environments where initiative and ownership are rewarded.

Resonate Attributes

At Resonate, we care about more than your experience on paper. We look for teammates who bring the right mindset and ways of working to help us do great work, together. The Resonators who thrive here embody these qualities:

• Proactive Problem-Solving: You spot challenges early and take initiative to solve them.
• Ownership: You take initiative, follow through, and hold yourself accountable.
• Collaboration: You value working with others and building strong, respectful relationships.
• Adaptability: You stay steady through change and adjust when needed.
• Growth Mindset: You’re open to learning, feedback, and trying new things.
• Customer