remote
Data Engineer - Rhombus Power
Data Engineer
Build and maintain scalable data pipelines and real‑time analytics platforms using Python, SQL, Airflow, and cloud services to enable predictive intelligence for defense and national security applications.
About the role
Key Responsibilities
- Design, develop, and operate robust ETL/ELT pipelines that ingest, transform, and store large volumes of structured and unstructured data.
- Implement real‑time streaming solutions using Kafka and Spark to support low‑latency predictive analytics.
- Automate workflow orchestration and scheduling with Apache Airflow, ensuring reliability and observability.
- Collaborate with data scientists and product teams to provide clean, well‑documented data sets for AI‑driven decision support.
- Maintain and optimize cloud infrastructure on AWS, including S3, Redshift, and Lambda functions.
- Monitor performance, troubleshoot issues, and continuously improve data quality and pipeline efficiency.
Requirements
- 3+ years of professional experience building data pipelines in Python and SQL.
- Hands‑on expertise with Apache Airflow, Kafka, and Spark (or similar big‑data frameworks).
- Strong knowledge of AWS services for data storage and processing.
- Experience designing data models and implementing ETL best practices.
- Ability to work cross‑functionally in a fast‑paced, mission‑critical environment.
Skills
pythonsqlawsapache sparkkafka