Business Intelligence Team Lead

2 days ago

Greater Toronto Area, Canada Robert Half Full time

A Robert Half client is seeking an experienced BI Engineer Team Lead to design, develop, and maintain scalable business intelligence solutions that empower data-driven decision-making across the organization. The ideal candidate will have strong technical expertise in data modeling, ETL processes, and visualization tools, combined with excellent problem-solving skills.

Key Responsibilities

- Data Architecture & Modeling:
- Design and implement robust data models for analytics and reporting.
- Optimize data structures for performance and scalability.
- ETL Development:
- Build and maintain ETL pipelines to extract, transform, and load data from multiple sources.
- Ensure data quality, integrity, and consistency across systems.
- Reporting & Visualization:
- Develop interactive dashboards and reports using BI tools (e.g., Power BI, Tableau, Looker).
- Collaborate with stakeholders to define KPIs and deliver actionable insights.
- Performance Optimization:
- Monitor and tune BI solutions for optimal performance.
- Implement best practices for query optimization and data governance.
- Collaboration & Support:
- Work closely with data analysts, data engineers, and business teams to understand requirements.
- Provide technical guidance and support for BI-related initiatives.

Required Qualifications

- Bachelor’s degree in Computer Science, Information Systems, or related field.
- 8+ years of experience in BI development and data engineering.
- Strong proficiency in SQL and relational databases (e.g., SQL Server, PostgreSQL).
- Hands-on experience with BI tools (Power BI, Tableau, or similar).
- Expertise in ETL tools and frameworks (SSIS, Informatica, or equivalent).
- Solid understanding of data warehousing concepts and dimensional modeling.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and their BI services.
- Excellent problem-solving and communication skills.

Preferred Skills

- Experience with Python or R for data manipulation.
- Knowledge of big data technologies (Spark, Hadoop).
- Exposure to machine learning or predictive analytics.

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