Job Summary
Responsible for building the business intelligence system for the company, based on the internal and external data structure. Responsible for leading the design and support of enterprise-wide business intelligence applications and architecture. Works with enterprise-wide business and IT senior management to understand and prioritize data and information requirements. Solves complex technical problems. Optimizes the performance of enterprise business intelligence tools by defining data to filter and index that add value to the user. Creates testing methodology and criteria. Designs and coordinates a curriculum for coaching and training customers in the use of business intelligence tools to enhance business decision-making capability. Develops standards, policies, and procedures for the form, structure, and attributes of the business intelligence tools and systems. Develops data/information quality metrics. Researches new technology and develops business cases to support enterprise-wide business intelligence solutions.
Job Responsibilities*
Data Preparation and Modeling
- Data Extraction & Transformation (ETL/ELT): Write and optimize complex SQL queries to extract data from various source systems (e.g., ERP, CRM, Web Analytics) and prepare it for reporting.
- Data Integrity: Design and maintain appropriate data models (e.g., star schemas) within the data warehouse to ensure data accuracy, consistency, and efficient query performance.
- Quality Assurance: Execute rigorous testing and validation procedures to guarantee the accuracy and reliability of all reported data and metrics.
2. Reporting, Visualization, and Analysis
- Dashboard Development: Design, develop, and maintain high-impact, interactive dashboards and reports using BI tools (Tableau, Power BI, Qlik, Looker) that communicate key performance indicators (KPIs) and track business progress.
- Deep-Dive Analysis: Conduct ad-hoc analysis and investigative research to answer specific business questions (e.g., why sales dropped in a specific region, what factors drive customer churn).
- Performance Monitoring: Proactively monitor business metrics, identifying root causes of performance deviations and articulating potential business impact to stakeholders.
3. Stakeholder Collaboration and Communication
- Requirements Gathering: Collaborate closely with business stakeholders (Sales, Marketing, Finance, Operations) to clearly understand their analytical needs and translate them into technical requirements and reporting solutions.
- Insight Presentation: Communicate complex findings and actionable recommendations to non-technical audiences using clear visual aids and storytelling techniques.
- Enablement: Provide training and support to end-users on how to effectively use BI tools and interpret reports, fostering a data-driven culture.
Qualifications
Technical Expertise
- SQL: Expert-level proficiency in writing, optimizing, and debugging advanced SQL queries.
- BI Tools: Strong, demonstrable experience with a major BI platform (e.g., Power BI, Tableau, QlikView/Sense) including data source integration, calculated field development (e.g., DAX, LOD expressions), and visualization best practices.
- Data Warehousing: Solid understanding of data warehousing concepts, ETL/ELT processes, and dimensional modeling.
- Data Sources: Familiarity with common data sources like cloud platforms (AWS, Azure, GCP) and business applications (e.g., Salesforce, Google Analytics).
- Programming (Desirable): Basic knowledge of Python or R for statistical analysis or data manipulation is a plus.
Interpersonal & Business Skills
- Analytical Aptitude: Exceptional critical thinking and analytical problem-solving abilities.
- Communication: Excellent written and verbal communication skills, with proven experience presenting complex data to diverse audiences.
- Business Acumen: Ability to quickly understand business processes, KPIs, and objectives within a corporate environment.
- Detail-Oriented: A strong commitment to data accuracy and attention to detail.