IT BI Manager

About the role

The IT BI Manager is a senior, full-stack member of the Data Analytics & Information Engineering (DAIE) team, responsible for reporting, analytics, and AI-enabled solutions across TTI’s business units. This role combines data analytics expertise with strong collaboration skills—SQL-based data preparation and Power BI reporting that delivers valuable solutions to the business. The position works across the enterprise rather than being tied to a specific business unit, and partners with the broader DAIE team to implement AI-enabled solutions such as Snowflake Cortex Analyst and Cortex Agents, Copilot agents, and related conversational or agentic tools for business consumption.

This role also implements advanced data modeling and single-source-of-truth data architecture efforts, champions data governance standards, and applies project management discipline to complex, multi-phase initiatives. This is a senior individual contributor role requiring deep technical expertise across the full data stack, from pipeline development through reporting and decision-support delivery.

Responsibilities

• Applies project management discipline to plan, sequence, and deliver complex, multi-phase data engineering and analytics initiatives, coordinating timelines, dependencies, and stakeholder expectations.
• Partners with business stakeholders and DAIE team members across business units to gather requirements, define technical solutions, and translate business needs into scalable pipeline and reporting architecture.
• Assists in implementing AI-enabled solutions for business consumption, such as Snowflake Cortex Analyst and Cortex Agents, Copilot agents, and related conversational or agentic tools, in partnership with the broader DAIE team.
• Collaborates with IT, data engineering, security, and business stakeholders to ensure solutions are scalable, supportable, secure, and aligned to enterprise standards.
• Implements advanced data modeling efforts—including dimensional modeling, semantic models, and predictive/statistical modeling—to support accurate, scalable analytics across the enterprise.
• Champions single-source-of-truth data architecture, consolidating redundant reports and legacy BI environments into unified, trusted enterprise data models.
• Establishes and reinforces data governance practices, including data quality standards, access controls, and documentation, to ensure solutions are secure, consistent, and auditable.
• Writes, tests, and troubleshoots complex SQL queries to access, transform, validate, and prepare data across multiple source systems.
• Builds, maintains, and enhances Power BI reports, dashboards, and semantic models—including enhanced visualizations—that support enterprise-wide business decision-making.
• Uses AI coding agents and related tools (e.g., GitHub Copilot) to accelerate development, testing, debugging, and documentation of pipelines, queries, reports, and automation.
• Assists with Snowflake data preparation, transformation, and semantic model development; contributes to and helps mature dbt-based transformation practices across the team.
• Monitors, troubleshoots, and optimizes scheduled data refreshes, pipeline jobs, and automated processes to minimize business disruption and technical debt.
• Serves as a technical resource and team player, sharing best practices in data engineering, automation, and analytics development, and supporting the professional growth of the broader team.
• Performs other related duties as assigned.

Expected Allocation of Time

• Data Discovery: 5%
• Data Ingestion: 10%
• Data Transformation: 15%
• Semantic Modeling: 20%
• Report/AI Solution Building/Maintenance: 20%
• Collaboration: 30%

Critical Success Factors

• Problem Solving — Ability to break down ambiguous, enterprise-scale data problems, troubleshoot root causes, and design solutions that are scalable and sustainable; the single most valued trait for this role.
• Team Player & Collaboration — Ability to share technical knowledge, support the growth of all team members, and work effectively alone or with cross-functional teams; highly valued by the team.
• Advanced Modeling & Data Architecture — Ability to design and lead advanced data models (dimensional, semantic, predictive/statistical) and single-source-of-truth architecture that the enterprise can rely on.
• AI Fluency — Genuine interest and hands-on ability in applying AI coding agents and AI-enabled business solutions (e.g., Copilot, Snowflake Cortex Analyst/Agents); a top must-have for this role.
• Project Management — Ability to plan, sequence, and manage complex, multi-phase technical initiatives, balancing timelines, dependencies, and stakeholder expectations.
• Data Governance — Ability to establish and enforce data quality, security, access, and documentation standards across pipelines and reporting solutions.
• Technical Depth — Strong experience across the full data stack, including pipeline engineering, orchestration, containerization, SQL, and Power BI reporting.
• Analytical Skills — Ability to understand data, write and interpret complex SQL, evaluate data quality, build reporting logic, and translate findings into practical recommendations.
• Business Partnership — Ability to build credibility with stakeholders across the enterprise, understand functional needs, and manage expectations without being tied to a single business unit.
• Ownership & Follow-Through — Ability to take end-to-end responsibility for complex, enterprise-wide pipeline and reporting projects from design through production support.
• Communication Skills — Ability to explain technical architecture, project updates, and data issues clearly to audiences with varying levels of technical knowledge.
• Technical Curiosity — Genuine interest in emerging data engineering tools, automation, AI-assisted development, and evolving best practices; willingness to learn quickly and apply new capabilities.

Requirements

• Bachelor’s degree along with 5–10 years of relevant experience in data engineering, analytics, or a related field is preferred; 3–5 years of experience is acceptable for candidates holding a bachelor’s degree in computer science, data engineering, or a closely related discipline. Master’s degree is a plus.
• Proficiency with SQL is required, including the ability to write, troubleshoot, and optimize complex queries for reporting, analytics, and data preparation.
• Proficiency with Power BI is required, including report and dashboard development, data modeling, and DAX in a business setting.
• Experience with advanced data modeling techniques—such as dimensional modeling, semantic modeling, or predictive/statistical modeling—and building single-source-of-truth data architecture is required.
• Experience using AI coding agents and AI-enabled business tools (e.g., GitHub Copilot, Snowflake Cortex Analyst/Agents, Copilot agents, or similar conversational/agentic solutions) is required.
• Experience applying data governance principles (e.g., data quality standards, access controls, documentation practices) is strongly preferred.
• Project management experience or demonstrated ability to plan and coordinate complex, multi-phase technical initiatives is strongly preferred.
• Experience with Snowflake and dbt is strongly preferred.
• Experience with Python is preferred, including the ability to build, test, and maintain automation scripts and integrations.
• Experience with Azure Data Factory, Docker, Kubernetes, and Prefect (or similar orchestration tools) is a plus.
• Ability to manage multiple priorities across enterprise-wide initiatives while maintaining consistent, high-quality technical delivery.
• Strong verbal and written communication skills with the ability to manage multiple priorities and perform well under pressure.
• Ability to work independently and as an integral part of a cross-functional team, acting as a collaborative team player and mentor to others.

Other Requirements

• Ability to travel (post-COVID) up to 10%. It is anticipated this position will travel 0-10%.

Physical Requirements

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift up to 30 pounds at times.