Data Engineer at Pruna AI merging data engineering, analytics engineering, and revenue operations. Working on intelligent automation and analytics for accessible and sustainable AI.
About the role
- Senior Data Engineer supporting the delivery and enhancement of enterprise data and analytics for DoD organizations. Collaborating with engineers and government partners on scalable, production-ready solutions.
Responsibilities
- Design, build, and maintain data pipelines and architectures to support data ingestion, transformation, integration, storage, and dissemination.
- Apply software engineering and ETL principles to ensure data accuracy, quality, consistency, and scalability.
- Integrate COTS and customer-developed tools within existing data frameworks to meet operational and analytical requirements.
- Collaborate with DataOps teams to prepare, automate, and optimize data workflows for real-time analytics.
- Implement and enforce data security policies, including data encryption and access controls.
- Monitor data quality and implement proactive alerting on data pipelines.
- Develop and maintain documentation for data pipelines, models, and governance policies.
- Provide Tier-2 and Tier-3 support for enterprise data products and services.
- Conduct root cause analysis for recurring issues and implement solutions to prevent future occurrences.
- Develop and maintain training materials and a centralized knowledge repository for data operations.
- Proactively communicate with customers regarding known issues and new features.
- Collect customer feedback to identify areas for improvement and enhance customer satisfaction.
- Foster a collaborative team environment that encourages innovation and continuous improvement.
- Ensure compliance with all applicable regulations related to data privacy and security.
Requirements
- Active Top Secret (TS) clearance with SCI eligibility
- Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or related technical discipline and 8–12 years of relevant experience OR Master’s degree in a related field and 6–10 years of relevant experience
- Minimum of 8 years of experience in data engineering or related roles
- Proven experience in designing and implementing data pipelines and architectures
- Experience with data quality monitoring tools and processes
- Excellent communication and interpersonal skills
- Experience developing and maintaining enterprise-scale data pipelines in cloud environments (AWS, Azure, or GCP)
- Experience implementing ETL/ELT processes and data orchestration frameworks
- Strong knowledge of ETL processes and data integration techniques
- Experience working with structured and unstructured data sources, including APIs, streaming platforms, and relational/non-relational databases
- Experience integrating data pipelines into DevSecOps CI/CD environments
Benefits
- Competitive compensation
- Health and Wellness programs
- Income Protection
- Paid Leave
- Retirement
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