Data Engineer

About the Company

Sand Technologies is a global Physical AI company using data and AI to make critical industries work better. We partner with governments, cities and enterprises to improve how essential systems operate across healthcare, water, energy, telecommunications and infrastructure.

Responsibilities

• Architect and build a secure, scalable urban data platform integrating multi-agency and infrastructure datasets
• Design resilient cloud-native architectures supporting batch, streaming, and near-real-time workloads
• Lead development of high-performance ingestion and transformation pipelines across legacy systems, APIs, and IoT
• Implement distributed and event-driven processing systems using Spark or Kafka
• Establish platform reliability standards including observability, data quality validation, and lineage
• Design and enforce strong data governance and access control frameworks
• Build modern lakehouse architectures to enable advanced analytics and machine learning
• Partner with data scientists and ML engineers to operationalize AI at scale
• Optimize platform performance, scalability, and cost efficiency

Requirements

• 3+ years designing and operating large-scale semi-distributed data platforms
• Proven experience architecting modern data systems like lakehouse or data mesh
• Deep expertise with distributed processing frameworks (Spark) and streaming systems (Kafka)
• Experience building secure, governed data environments in regulated or government sectors
• Proficiency in Python, SQL, and dbt
• Experience with cloud providers (AWS, Azure, or GCP)
• Knowledge of U.S. public sector data privacy and security requirements (e.g., HIPAA, CJIS, FERPA)
• Ability to travel to client sites in Baltimore at least 4 days a week