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Resonate is a leading provider of AI-powered consumer data, intelligence, and technology for enterprise marketers. The company's SaaS platform Ignite and Data-as-a-Service offerings deliver insights into consumer motivations, values, and behaviors.
This Data Engineer role focuses on designing, building, and maintaining the ETL/ELT pipelines that power the entire Resonate business. You'll work hands-on with Spark and Scala on AWS EMR, handling terabyte and petabyte-scale datasets across S3 and Snowflake. The team is genuinely committed to integrating generative AI into the engineering workflow, not as a side project but as a core part of how work gets done.
Key responsibilities include:
- Designing and maintaining production ETL/ELT pipelines at massive scale
- Tuning multi-terabyte Spark applications for performance and cost optimization
- Debugging complex issues that only surface at production scale
- Partnering with senior engineers and product management on pipeline architecture
- Monitoring pipeline health in Grafana and addressing data quality issues
- Writing clean, testable code with comprehensive unit and integration tests
- Leveraging Gen AI tools across pipeline development and day-to-day engineering
- Participating in code reviews, technical design discussions, and sprint planning
- Supporting production operations including on-call rotation and incident response
Required qualifications: 5+ years professional software or data engineering experience; 3+ years hands-on with Spark and Scala (DataFrame and Dataset APIs); proven experience tuning Spark at multi-terabyte or petabyte scale in production; real debugging experience in big data ecosystems; solid relational database knowledge; working knowledge of AWS (EMR, S3, Lambda), Kafka, Snowflake, Grafana, Hadoop, Elastic Stack, and Docker; strong grasp of full software development lifecycle and solution architecture; genuine enthusiasm for using generative AI to accelerate data engineering work.
Strong signals include hands-on experience building big data pipelines with Gen AI, probabilistic data structures, high cardinality data systems at scale, and a CS degree or equivalent.
