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About
Nakupuna Prime is looking for a Senior Data Engineer to design, build, and maintain data pipelines and data warehouse infrastructure to ensure reliable, scalable, and secure data integration that supports reporting and analytics. This senior role leads data architecture and pipeline standards, provides technical direction, and mentors engineers to ensure secure, reliable, and scalable data products. This effort supports the United States Naval Community College (USNCC). Responsibilities
The following reflects management's definition of essential functions for this job but does not restrict the tasks that may be assigned. Management may assign additional duties and responsibilities to this job at any time due to reasonable accommodation or other reasons. Design, build, and maintain ETL/ELT pipelines using Python and SQL to ingest data from Salesforce Education Cloud, flat files, and API endpoints into the data warehouse. Implement robust error handling, logging, and automated monitoring to detect and track data quality issues. Define schemas and curate unified student datasets with targeted completeness and accuracy for downstream reporting and modeling. Optimize AWS Redshift and PostgreSQL performance through tuning, query optimization, and storage management. Serve as escalation point for complex data discrepancies and pipeline failures; provide root-cause analysis and permanent fixes. Coordinate with analysts and BI developers to validate transformations and resolve mismatches. Lead design reviews for data pipelines and warehouse changes; establish standards for reliability, security, and performance. Architect and maintain monitoring, alerting, and data quality frameworks to detect issues before downstream impact. Mentor data engineers and lead root-cause analysis for high-impact pipeline failures or data discrepancies. Qualifications
Qualification/Skills
: Expert-level data pipeline architecture and engineering (ETL/ELT), including reliability patterns, observability, and automation. Deep SQL and warehouse performance tuning expertise (Redshift/PostgreSQL), including schema design and query optimization. Proven experience implementing data quality frameworks (rules, anomaly detection, reconciliation) and leading remediation efforts. Ability to lead technical design reviews, incident response/root-cause analysis, and long-term platform improvements. Leadership skills to mentor engineers and coordinate cross-functionally with BI and data science teams. Education and Experience:
This position requires a bachelor's degree in Engineering, Computer Science, or equivalent. The following are desirable levels of experience: 10+ years of data engineering experience designing enterprise data platforms and pipelines Demonstrated expertise in AWS Redshift/PostgreSQL performance tuning and cost optimization Experience architecting data quality frameworks and automated monitoring/alerting at scale Experience establishing data governance standards, schemas, and integration patterns across multiple sources Demonstrated experience mentoring engineers and leading technical reviews and incident response Military Installation Access and Security Clearance:
This position requires access to military installations. Must be able to qualify for and obtain base access and pass a background check. Must be a U.S. citizen. Location:
This position is hybrid. Work will be done on site at least three (3) days a week in Arlington, VA. Remote candidates will be considered. Occasional travel may be required. Physical Requirements:
The ideal candidate must at a minimum be able to meet the following physical requirements of the job
with or without a reasonable accommodation: Ability to perform repetitive motions with the hands, wrists, and fingers. Ability to engage in and follow audible communications in emergency situations. Ability to sit for prolonged periods at a desk and working on a computer. Ability to walk for extended periods throughout the work day including moving between buildings and covering long distances by foot.
Languages
- English
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