Data Engineer: Scalable Lakehouse & Real-Time Analytics

jobr.pro; Baltimore (MD); On-site; USD 110,000 - 180,000; Full time

Job summary

Sand Technologies is seeking a Data Engineer to design, build, and maintain scalable data architectures that underpin decision-support applications. You will work with hybrid data architectures and cloud-native environments across AWS, Azure, and GCP, enabling analytics, ML, and AI workflows.

The role emphasizes a data-as-a-product mindset with strong testing, reliability, observability, and performance requirements.

Qualifications

• 3+ years designing and operating large-scale data platforms in cloud or hybrid environments.
• Experience with lakehouse or data mesh architectures for analytical and operational workloads.
• Hands-on with distributed processing (Spark) and streaming (Kafka) systems.
• Strong data governance, security, encryption, and auditability practices.
• Experience with AWS, Azure, or GCP and IaC/CI/CD.
• Ability to work with multi-stakeholder teams in regulated environments.

Responsibilities

• Architect and build secure, scalable urban data platform integrating multiple datasets.
• Design cloud-native architectures supporting batch, streaming, and real-time workloads.
• Lead high-performance ingestion and transformation pipelines across diverse data sources.
• Implement distributed processing systems (Spark, Kafka) for analytics and operations.
• Establish observability, data quality, lineage, monitoring, and SLAs/SLOs.
• Enforce data governance, RBAC, encryption, and secure data handling.
• Build lakehouse architectures enabling GIS and production-grade ML.
• Collaborate with data scientists and ML engineers to operationalize AI at scale.
• Optimize platform performance, scalability, and cost as adoption grows.
• Mentor engineers and contribute to long-term architectural direction.

Skills

Python

SQL

Databricks

Spark

Data modeling

Cloud platforms

DevOps / CI/CD

RBAC / security

Communication

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

dbt

Docker

Airflow

Kubernetes

Job description

Sand Technologies is seeking a Data Engineer to design, build, and maintain scalable data architectures that underpin decision-support applications. You will work with hybrid data architectures and cloud-native environments across AWS, Azure, and GCP, enabling analytics, ML, and AI workflows.

The role emphasizes a data-as-a-product mindset with strong testing, reliability, observability, and performance requirements.