Senior Data Engineer, Data Analytics

Accountabilities: Collaborate with robotics software and hardware engineering teams to define, collect, structure, and curate the data required for analytics, system monitoring, and debugging. Design, develop, maintain, and optimize scalable ETL pipelines that transform raw robot logs and telemetry into structured, reliable datasets. Leverage Apache Spark, Airflow or equivalent orchestration technologies, and AWS data services to build and manage production-grade data processing workflows. Own and maintain gold-layer datasets supporting fleet dashboards, hardware reliability models, operational reporting, and business performance metrics. Establish and maintain data freshness service-level agreements (SLAs), documentation standards, monitoring systems, and quality controls to ensure dependable data products. Implement data validation checks, schema evolution strategies, and metadata management practices using internal data registries and cataloging systems. Collaborate with analytics, reliability, and machine learning teams to design efficient data models that meet their analytical and operational requirements. Optimize logical data models and physical data partitioning to improve query performance across analytical engines and playback or root-cause analysis tools. Ensure efficient storage, processing, and accessibility of structured, numerical, and potentially multimodal robotics datasets. Contribute to shared software libraries and APIs using Python, Java, or C++ to improve data capture, serialization, and consumption when needed. Promote best practices in data architecture, pipeline reliability, dataset versioning, and data governance across the broader engineering organization. Work closely with cross-functional stakeholders to translate technical and operational requirements into scalable data platform solutions. Requirements At least 5 years of professional experience as a Data Engineer or in a similar role building, deploying, and maintaining production data pipelines. Strong proficiency in Apache Spark or an equivalent distributed data processing framework. Programming experience in Python, Java, and/or Scala, with the ability to develop and maintain reliable data processing solutions. Hands-on experience with data orchestration platforms such as Apache Airflow, Dagster, Prefect, or equivalent technologies. Strong knowledge of data serialization and storage formats, including Avro, Parquet, and structured or numerical datasets. Familiarity with modern data lake table formats and architectures, such as Apache Iceberg, Delta Lake, and medallion architecture. Solid understanding of data modeling, schema evolution, data quality management, and metadata governance best practices. Ability to design logical data models and physical data partitions that optimize performance for analytical queries, data playback, and root-cause investigations. Understanding of how to structure and manage large-scale datasets generated by distributed systems and physical devices. Experience collaborating with software engineering, hardware engineering, analytics, and data science teams in fast-paced technical environments. Strong analytical and problem-solving skills, with the ability to investigate complex data challenges and develop practical solutions. Excellent communication and collaboration skills, including the ability to explain technical concepts and align data architecture decisions with different stakeholders. Nice to have: Experience with data versioning strategies and immutable dataset architectures, including Apache Iceberg or Delta Lake. Experience working with computer vision and perception datasets, including RGB images, depth data, point clouds, and other multimodal outputs. Familiarity with processing, storing, and querying large-scale multimodal datasets efficiently. Knowledge of C++ and willingness to contribute to lightweight logging, data capture, or serialization libraries. Experience with data cataloging platforms, metadata management, and internal data registries. Work authorization: Applicants must be currently authorized to work in the United States, as all positions are US-based. Benefits Competitive salary: Annual base compensation ranging from $175,000 to $274,000 USD , depending on experience, skills, qualifications, and geographic market. Retirement savings: 401(k) plan with a generous 6% company match . Equity compensation: Eligibility for company stock options. Comprehensive healthcare: 100% company-paid medical, dental, and vision insurance for employees. Disability coverage: Company-paid short-term and long-term disability insurance. Immediate benefits eligibility: Employees become eligible for benefits from their first day of employment. Employee assistance: Access to an Employee Assistance Program (EAP) supporting personal and professional well-being. Flexible paid time off: Exempt employees benefit from flexible, unlimited PTO, while non-exempt employees receive 10 vacation days and paid sick leave. Paid holidays: 12 company holidays annually, including a winter shutdown. Parental leave: Generous paid parental leave programs. Professional development: Access to training, career development opportunities, and tuition reimbursement programs. Flexible work arrangements: Fully remote working options, with hybrid arrangements available for employees within commuting distance of offices in Salem, Oregon; Pittsburgh, Pennsylvania; or Fremont, California. On-site perks: Catered lunches four times per week, along with healthy snacks and refreshments at the Salem and Pittsburgh locations. Additional compensation: Eligibility for annual discretionary bonuses for qualifying roles. Relocation assistance: Available for eligible positions. Meaningful technical impact: Opportunity to work with cutting-edge humanoid robotics technology and contribute to innovative data infrastructure at the intersection of physical systems and advanced analytics. Collaborative environment: Work alongside talented robotics engineers, software developers, and data scientists in a small, high-impact team.