Data Engineer at sandtechholdingslimited

Location: Baltimore, Maryland
Posted: Jul 9, 2026

Description

Sand Technologies is seeking a Data Engineer to design, build, and maintain scalable data architecture for decision-support applications. The role involves creating secure, scalable urban data platforms, leading pipeline development, implementing distributed processing systems, establishing reliability standards, enforcing data governance, and partnering with data scientists and ML engineers. The ideal candidate will have extensive experience in cloud-native environments, distributed processing frameworks like Spark, and strong proficiency in Python, SQL, and DBT.

Required Skills

Python
SQL
dbt
AWS
Azure
GCP
Spark
Kafka
Docker
PySpark
Databricks
dbt

Additional Information

Required Previous Experiences: 3+ years designing and operating large-scale semi-distributed data platforms (hybrid centralised and distributed) in cloud or hybrid environments.
Proven experience architecting modern data systems (lakehouse, data mesh, or equivalent) supporting both analytical (descriptive and predictive) and operational workloads.
Deep hands-on expertise with distributed processing frameworks (e.g., Spark) and streaming/event systems (e.g., Kafka or similar).
Strong experience building secure, governed data environments with robust access controls, encryption, lineage, and audit capabilities.
Experience designing secure data platforms in regulated or government environments, with strong understanding of compliance, auditability, and data protection standards.
Experience integrating heterogeneous data sources, including legacy systems, APIs, telemetry/IoT systems, and relational databases.
Demonstrated ability to design highly available, observable, production-grade data systems.
Experience enabling machine learning and advanced analytics through robust data infrastructure and feature pipelines.
Experience deploying and operating solutions in AWS, Azure, or GCP, including CI/CD and infrastructure-as-code is beneficial.
Experience designing data platforms in U.S. public sector or highly regulated environments, with working knowledge of applicable federal and state data privacy and security requirements (e.g., HIPAA, CJIS, FERPA, state-level privacy acts), and the ability to embed compliance, auditability, and data governance principles into architectural design.
Preferred Qualifications: Strong proficiency in Python, SQL, and ideally DBT with a track record of writing clean, production-quality code.
CI/CD and infrastructure-as-code is beneficial.