LightFeather is hiring a
Data Engineering Lead, Remote - Worldwide

Summary

LightFeather is seeking a Data Engineering Lead to spearhead data modeling initiatives, utilizing various tools like PowerBI, Airflow, Erwin, GitLab, and Python. The position is full-time and remote.

Requirements

• US Citizenship
• Active or prior clearance at the Public Trust level or above. IRS or Department of Treasury clearance preferred. If prior, must be within the last 2 years
• Bachelor’s degree preferred or equivalent experience
• 9+ years of hands-on experience in data modeling, analytics solution delivery, and dashboard development
• Proficiency in PowerBI, Airflow, Erwin, GitLab, and Python
• Proficiency in Erwin or similar technologies
• Strong understanding of GitHub branching strategies and version control best practices
• Experience in Agile methodologies and an agile data science work environment
• Demonstrated ability in analytics and exploratory data analysis
• Proven track record of delivering efficient and scalable data pipelines
• Excellent communication and leadership skills

Responsibilities

• Develop conceptual, logical, and physical data models that support data analysis and reporting
• Ensure data models are optimized for performance and scalability across various platforms and technologies
• Establish and enforce data modeling standards, best practices, and methodologies
• Manage the lifecycle of data models, including maintenance, updates, and documentation
• Assist in data integration, data quality, and data governance initiatives
• Provide technical leadership and mentorship to junior data modeling staff
• Develop and maintain PowerBI dashboards showcasing model performance metrics
• Utilize Airflow for effective model orchestration, ensuring seamless data workflows and processes
• Develop and implement a robust GitHub branching strategy to enhance collaboration and efficiency
• Employ Python or similar programming languages to develop AI and machine learning models
• Foster an agile data science work environment, promoting rapid iteration, collaboration, and continuous improvement
• Lead exploratory data analysis efforts to uncover new insights and opportunities for data-driven decision-making