About the Role As a Lead Data & BI Automation Analyst at Obviant, you will lead high-impact analytics and data pipeline initiatives that scale our decision-making capabilities, streamline internal workflows, and optimize overall business performance. You will act as a trusted technical partner, designing automated reporting frameworks, building robust data delivery mechanisms, and replacing manual workflows with resilient, self-service data systems for Obviant.

What You’ll Do

• BI Automation & Scalable Systems: Architect, deploy, and maintain automated reporting frameworks, self-updating dashboards, and data delivery pipelines using modern BI tools and orchestrators.
• Workflow & Process Optimization: Audit existing manual reporting processes across teams, replacing fragmented spreadsheets and ad-hoc queries with automated, production-grade scripts and data workflows to determine requirements for fully automated systems.
• Stakeholder Alignment & Delivery: Interface directly with business leaders, cross-functional teams, and government partners to conduct targeted analytics, understand operational workflows, and translate complex business needs into scalable, automated solutions.
• Data Pipeline Collaboration: Partner closely with Data Engineering to design and optimize analytical data models, automated data transformations, and scheduled ELT/ETL jobs (e.g., via dbt or Airflow).
• Cross-Functional Analytics: Collaborate with Product, Marketing, and Operations teams to translate complex, automated data models into clear, actionable, self-service business insights.
• Data Strategy & Architecture Expansion: Pioneer automated data quality frameworks, monitoring systems, and scalable metrics trees as obviant.com continues to expand.
  

What You Need

• Experience: 4+ years of professional experience in data analytics, BI engineering, or data automation, with a proven track record of automating operational workflows.
• Education: Degree in Computer Science, Information Systems, Mathematics, Statistics, Economics, or a field with a strong quantitative/technical focus preferred.
• Data & Transformation Mastery: Advanced proficiency in SQL and experience with modern transformation layer tools (e.g., dbt) for building scheduled, production-grade data models.