Senior Business Intelligence Engineering and Data Manager
$120,000–$120,000 year
On-siteColumbus, Ohio, United States
Job Summary
Lead technical execution of enterprise analytics initiatives by setting architectural direction for scalable, governed BI platforms and translating ambiguous business needs into durable roadmaps. Provide people leadership for the BI Engineering and Data Products team, managing developers through performance management, coaching, and workforce planning while serving as the escalation point for complex cross-functional delivery issues. Decompose and lead execution of complex BI engineering problems, overseeing pipeline quality from semantic layers through dashboards by enforcing standards for data modeling, testing, documentation, and CI/CD. Design and evolve shared semantic layers and metrics frameworks, partnering with Data Engineering and IT teams to align solutions with enterprise data platforms. Quantify the impact of BI initiatives to inform prioritization and investment decisions, ensuring platforms operate as stable, well-governed systems with clear ownership and observability.
Required Qualifications
- Bachelor's Degree in computer science, engineering, analytics, or related field
- 7-9 years hands on experience in a data engineering or analytics related role
- 4-6 years managing a technical team
- 7-9 years Advanced SQL development, including complex transformations, performance optimization, and data modeling
- 4-6 years Experience with modern cloud data warehouses (e.g., Snowflake or similar)
- 4-6 years Experience using Python or other programming languages for data transformation, automation, or analytics workflows
- 4-6 years Experience with modern analytics engineering tools (e.g., dbt, FiveTran) and CI/CD practices
- Expert-level SQL knowledge, including advanced query optimization, window functions, CTEs, nested queries, and complex transformations used in enterprise analytics workflows
- High (High proficiency) Advanced proficiency in Python or similar programming languages for analytics engineering, automation, workflow orchestration, and operational reporting
- High (High proficiency) Ability to technically scope, decompose, and solve abstract analytical problems by translating ambiguous business needs into well-defined BI engineering designs using computer science and analytics engineering principles
- High (High proficiency) Deep knowledge of BI and analytics engineering architecture, including the design and evolution of governed semantic layers, metrics frameworks, and reusable analytics components
- High (High proficiency) Strong understanding of data warehouse architecture and data modeling best practices, including dimensional modeling, performance optimization, and alignment with upstream ingestion patterns
- Medium (Medium proficiency) Experience leading teams responsible for enterprise BI platforms, dashboards, and downstream data products built on governed semantic layers
- Medium (Medium proficiency) Ability to lead technical scoping, estimation, and business case refinement, including defining and comparing quantifiable value, complexity, and architectural impact across analytics use cases
- Medium (Medium proficiency) Demonstrated people management skills, including coaching, performance management, mentoring senior technical talent, and workforce development
- Medium (Medium proficiency) Strong communication and stakeholder management skills, with the ability to translate between business objectives and technical design decisions
- Medium (Medium proficiency) Sound architectural judgment to balance near-term delivery with long-term scalability, maintainability, and platform consistency
- Medium (Medium proficiency) Experience administering and governing BI platforms (e.g., Tableau Cloud), including site management, permissions, content organization, certification, automation, and enforcement of reporting standards
- Medium (Medium proficiency) Familiarity with modern data engineering tools, CI/CD concepts, and version control practices as they relate to analytics engineering and BI workflows
- You are required to work in the office at least 4 days a week
- pre-employment screenings, including background checks and/or drug screenings
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