Senior Data Engineer, First Resonance

• We’re looking for a hands-on engineer who thrives on building robust, scalable systems and is passionate about supporting the future of hardware through intelligent data solutions and advanced AI techniques
• If you're excited about climate innovation, space exploration, and the power of data to transform manufacturing, this is your place
• 5+ years of experience in Data Engineering or related technical fields
• Advanced proficiency in Python, SQL, and modern orchestration tools (e.g., Airflow, Dagster)
• Strong background in Postgres and other OLTP/relational databases
• Deep experience with data transformation using dbt and working with cloud data warehouses (e.g., Snowflake, BigQuery)
• Extensive experience with GraphQL APIs and integrating diverse data sources
• Design and implement real-time and batch processing systems using tools such as Apache Kafka, Kafka Connect, and Apache Flink
• Expertise in building and maintaining cloud-native data infrastructure on AWS
• Experience in Rust, Go, or similar high performance language
• Familiarity with MLOps workflows, including feature engineering, data versioning, and model deployment pipelines
• Strong understanding of data lifecycle, data governance, and CI/CD principles
• Proven track record of cross-functional collaboration and stakeholder alignment
• Understanding of regulatory data compliance (e.g., SOC2, GDPR) and data governance frameworks

Desirable

• First Resonance is seeking a Senior Data Engineer to join our mission of bringing the ION Factory OS to next-generation hardware builders around the globe
• As a senior member of our engineering team, you'll play a pivotal role in shaping the data infrastructure that empowers manufacturers working on electric aircraft, autonomous vehicles, robotics, and space systems
• Architect, build, and maintain scalable data pipelines for structured and unstructured data across cloud-native infrastructure
• Collaborate with DevOps to manage and optimize data infrastructure for performance, cost-efficiency, and reliability
• Implement robust data modeling and transformation ensuring data quality and lineage across our analytics ecosystem
• Architect and support the various data requirements from numerous internal and external systems
• Collaborate on building Agentic AI frameworks and ensuring the supporting tools and data infrastructure are in place
• Partner with product, engineering, and analytics teams to enable data access and deliver customer-facing data products