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
Manage a team of 8-15 direct reports, providing guidance and support for their professional development
Foster a collaborative team environment that encourages innovation and continuous improvement
Ensure compliance with all applicable regulations related to data privacy and security

Active Secret clearance
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
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
Demonstrated experience leading and mentoring technical teams

Senior Data Engineer – Lead

Key skills