redhorsecorp - Lead Data Engineer
Requirements
• Security Clearance: Must be a U.S. Citizen with a current, active U.S. Government Secret clearance. (Applicants without an active Secret clearance cannot be considered). • Experience Level: Minimum of 8+ years of professional experience in data engineering, building enterprise-scale data platforms and pipelines. • Technical Guidance: Demonstrated experience providing technical mentorship, performing code reviews, and providing day-to-day technical task oversight to other engineers. • Databricks: Proven, hands-on experience designing and optimizing data transformation workflows in Databricks. • Python/PySpark & SQL: Advanced skills in modular, object-oriented Python/PySpark scripting and extensive experience writing, tuning, and optimizing complex SQL queries. • Data Visualization: Proven experience building functional, user-centric reports and dashboards using modern data visualization tools. • We encourage all candidates who meet the basic requirements to apply, even if you do not have any of the following experience: • Hands-on experience with Apache Spark and distributed computing frameworks. • Familiarity with modern agile and DevOps tools such as GitLab Jira. • Experience working with DoD, defense, or intelligence community data environments and compliance standards. • Knowledge of data governance, metadata management, and data cataloging frameworks. • Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related technical discipline. • The salary range provided for this position represents the anticipated base salary for successful candidates. Actual compensation will be determined based on a variety of factors, including relevant experience, education, certifications, skills, security clearance level, geographic location, market conditions, and internal equity. In addition to base salary, eligible employees may participate in Redhorse's comprehensive benefits programs and may be eligible for performance-based or other incentive compensation, where applicable.
Responsibilities
• Technical Leadership & Task Oversight: Provide day-to-day task prioritization and technical direction to team members; lead code reviews, ensure design best practices, and mentor engineers in modular Python development and SQL optimization. • Requirements Development & Architecture: Work directly with government stakeholders to elicit, refine, and translate complex mission requirements into robust technical specifications, interface designs, and scalable data models. • Pipeline & Platform Development: Architect, develop, and optimize high-throughput ETL/ELT workflows using Databricks; maintain, refactor, and enhance existing Python and SQL codebases for performance, stability, and security. • Pipeline Diagnostics & Troubleshooting: Identify pipeline bottlenecks, debug complex data workflows, and implement automated solutions to enhance pipeline reliability and data integrity. • Cross-Functional Collaboration: Partner closely with government product owners, data scientists, Data Analysts, and technical peers to document architecture, coordinate technical sprints, and communicate engineering trade-offs to technical and non-technical audiences. • Technical Documentation: Develop new and maintain existing pipeline architecture documentation relating to pipeline code architecture and configurations to ensure high system reliability and seamless team onboarding.
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