Senior Data Engineer

About the role

Join our Data Engineering team as a Senior Data Engineer, where you will architect, build, and scale the foundational data infrastructure that powers our global fleet's analytics, machine learning models, and real-time business intelligence. In this remote position, you will own the end-to-end design, delivery, and operation of major data products, partner with engineering, product, and business stakeholders, and solve difficult data engineering problems. You will also influence the technical direction of the data products you own, set a high quality bar, and lead projects that improve the team's engineering and operational excellence. Key missions: Conception, delivery, and operation of major data products, including high-throughput ETL/ELT pipelines.. Collaboration with engineering, product, and business stakeholders to clarify requirements and drive projects from design through production launch.. Mentoring other engineers, providing actionable technical feedback, and participating in interviewing and hiring. Profile: - Strong understanding of data modeling, ETL/ELT architecture, schema design, and transformation frameworks such as dbt - Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience - Experience establishing or improving data quality, testing, observability, lineage, and operational practices - Hands-on experience with distributed processing or streaming technologies such as Spark, Flink, or Kafka - A track record of independently delivering and operating significant production data products end to end - Experience writing technical design documents and communicating complex decisions to technical and non-technical stakeholders - Experience using AI-assisted development tools to support coding, debugging, testing, documentation, technical exploration, and analysis - Experience designing reliable workflows using orchestration tools such as Airflow - 5+ years of relevant industry experience in data engineering, distributed systems, or a related field - Strong technical judgment and experience making trade-offs among performance, reliability, scalability, maintainability, and cost - Ability to validate AI-assisted outputs, identifying risks and failure modes, protecting sensitive information, and knowing when deeper manual review is required - Deep experience building and scaling cloud-based data platforms, preferably using AWS and Snowflake - Expertise in developing, optimizing, and debugging complex data transformations using Python and high-performance SQL - Familiarity with modern data governance practices, including cataloging, data classification, PII masking, privacy controls, and access management - Experience with technologies such as Iceberg, Debezium, or infrastructure-as-code tools such as Terraform is a plus