Business Intelligence Manager

Role Overview We are seeking an experienced Business Intelligence Manager to lead the development and execution of our business intelligence strategy, overseeing the design, implementation, and optimization of BI solutions within our Databricks Data Lakehouse environment. This role will manage a team of data engineers, data analysts, and data scientist, collaborate with cross-functional stakeholders, and deliver scalable dashboards, reports, and insights to drive business performance. The ideal candidate is an experienced leader with expertise in BI tools, Databricks, and data analytics, capable of translating complex data into actionable business strategies.

Candidate Profile

• Skills & Qualifications
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
• 3+ years of experience in data science, with a focus on AI and machine learning.
• Hands-on experience with Databricks, including notebooks, MLflow, and Spark ML.
• Proven track record of building and deploying machine learning models in a production environment.
• Proficiency in Python and/or R for data science workflows.
• Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). 
• Experience with SQL for querying data in Databricks SQL Analytics.
• Familiarity with Delta Lake and Apache Spark for large-scale data processing.
• Understanding of cloud platforms (AWS, Azure, or GCP) hosting Databricks.
• Experience integrating AI models with BI tools like Tableau, Power BI, or Databricks’ visualization tools.
• Databricks Certified Data Scientist or Data Engineer certification is a plus.
• Excellent communication skills to translate technical insights for non-technical stakeholders.
• Strong problem-solving and analytical skills.
• Ability to work collaboratively in a cross-functional team.
• Work Environment
• Occasional travel necessary to accommodate for global and regional meetings, workshops or training.
• Ability to occasionally join calls before / after traditional office hours