Business Intelligence Specialist

Job Purpose

Business Intelligence Specialist role is to transform raw data into meaningful insights and actionable intelligence through the design, implementation, and management of BI tools and systems. By leveraging data analytics, visualization, and reporting techniques, the BI Specialist enables informed decision-making and drives strategic business improvements

Essential Roles and Responsibilities

Dashboard Development & Management:

Design, develop, and maintain interactive Power BI dashboards and reports based on business requirements.

Collaborate with stakeholders to gather and define data requirements, ensuring dashboards effectively address business needs.

Create data visualizations and provide actionable insights to guide decision-making processes.

Implement and manage data refresh schedules and ensure data accuracy and timeliness.

Data Engineering:

Design, build, and maintain robust ETL (Extract, Transform, Load) processes to integrate data from various sources into data warehouses or data lakes.

Optimize data models and query performance to support high-performance data retrieval and reporting.

Develop and manage data pipelines and workflows to ensure data integrity and consistency.

Work with databases (e.g., AWS Redshift, SQL Server, Azure SQL, etc.) to perform data manipulation, cleansing, and validation tasks.

Ongoing Support & Improvement:

Provide technical support for existing Power BI reports and dashboards, addressing issues and making necessary updates.

Continuously monitor and troubleshoot data-related problems, implementing solutions as needed.

Conduct regular reviews of data processes and dashboard performance, recommending improvements and optimizations.

Stay up-to-date with the latest Power BI features and best practices, incorporating new functionalities into dashboard development as appropriate.

Collaboration & Communication:

Work closely with data analysts, business analysts, and other stakeholders to ensure alignment of data projects with business objectives.

Document data processes, dashboard functionalities, and system configurations.

Provide training and support to end-users to facilitate effective use of Power BI reports and dashboards.

Technology Selection:

Evaluate and recommend appropriate technologies, tools, and frameworks for data governance principles and processes.

Continuous Learning:

Stay updated with the latest trends, tools, and techniques in data engineering to drive innovation and improvements within the organization.

Project Management:

Contribute to data governance projects, collaborating with cross-functional teams to deliver on time and within scope.

Job Requirements

Education:

Bachelor’s degree in computer science, Data Science, Information Systems, Engineering, or a related field.

Certification in Microsoft Power BI is mandatory.

2. Experience:

Minimum of 8+ years in Data Analytics with proficient in designing and implementing interactive dashboards and reports using Power BI.

Strong analytical skills with the ability to interpret complex data and present it in a clear and concise manner.

Solid understanding of data warehousing concepts and data modeling.

Experience with DAX (Data Analysis Expressions) and M language for Power Query.

Knowledge of data visualization best practices and trends.

Excellent problem-solving abilities and attention to detail.

Strong communication and interpersonal skills, with the ability to work effectively in a team environment.

Proactive and self-motivated with a passion for continuous learning and improvement.

Experience with cloud-based data platforms such as Azure Data Factory, AWS Redshift.

Knowledge of additional programming languages such as Python or R for data analysis.

Understanding of data architecture principles, including data warehouse design, data lakes, and data virtualization, to support effective data governance practices.

3. Communication and Collaboration:

Excellent communication skills to work effectively with cross-functional teams and translate business requirements into analytical solutions.

4. Adaptability and Learning:

Willingness to learn and adapt to new technologies and tools in the evolving data analytics and data engineering landscape.

5. Project Management:

Capability to manage projects, timelines, and priorities while collaborating with multiple stakeholders.