Senior Data Engineer – Platform Engineering

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5 days ago

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Atreides

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SaaS • Government • Enterprise

Atreides is a SaaS analytics company that transforms petabytes of geospatial and geotemporal data into clear, actionable intelligence. Their platform ingests and fuses land, sea, air, cyber, and space datasets and applies proprietary attribution, modeling, and behavioral analytics to surface relationships, patterns, and anomalies in near real-time. Atreides serves defense, public sector, and commercial customers, enabling faster strategic and tactical decision-making by delivering curated, explainable insights rather than raw bulk data.

11 - 50 employees

☁️ SaaS

🏛️ Government

🏢 Enterprise

📋 Description

• Architect scalable systems for ingesting, processing, and querying high-volume datasets. • Lead development of core data infrastructure components, including scalable data pipelines. • Design, implement, and maintain robust orchestration frameworks (e.g., Apache Airflow, Dagster, Prefect) to schedule, monitor, and manage large-scale data workflows. • Develop and maintain self-service platform SDKs, libraries, and tooling to empower other engineering and analytics teams to build, deploy, and monitor pipelines independently. • Optimize the performance, cost-efficiency, and reliability of platform services. • Ensure high availability, observability, and compliance for platform components. • Implement secure data handling practices and fault-tolerant systems. • Mentor junior engineers and provide code reviews, guidance, and architectural leadership. • Collaborate with analytics and customer-facing teams to align infrastructure with use-case requirements.

🎯 Requirements

• 5+ years of experience building and maintaining production-grade data systems. • Deep expertise in distributed processing frameworks (e.g., Spark, Flink, Kafka) and cloud architecture. • Advanced proficiency in Python and SQL (especially Spark SQL). • Experience developing internal platform tooling or SDKs that enable self-service data and workflow management. • Experience with geospatial data processing, formats, and services (e.g., Apache Sedona). • Strong understanding of CI/CD workflows, observability tools, and platform reliability engineering.

🏖️ Benefits

• Comprehensive health, dental, and vision insurance plans • Flexible hybrid work environment • Additional benefits like flexible hours, work travel opportunities, competitive vacation time and parental leave