About Position

AI Business Intelligence (BI) Engineer

As an AI Business Intelligence (BI) Engineer, you will be responsible for building and maintaining BI dashboards, reports, and analytics solutions using Tableau and Quick Sight. You will collaborate with data scientists, data engineers, and business stakeholders to integrate AI-driven insights into BI processes and ensure data-driven decision-making across the organization. Additionally, you will design and implement solutions using AWS cloud technologies and leverage Python for data processing and automation.

Expertise You'll Bring

Must have:

• 3+ years of experience in business intelligence, data analytics, and AI implementation.
• Strong experience with BI tools (Tableau, Quick Sight, Power BI, etc.).
• Proficiency in Python for data processing, automation, and machine learning.
• Experience with AWS services (S3, Redshift, Lambda, Glue, etc.) for building cloud-based BI and AI solutions.
• Hands-on experience integrating AI or machine learning models into BI workflows.
• Experience with data warehousing concepts and tools (Redshift, Snowflake, etc.).

Technical Skills:

• Strong understanding of BI tools and dashboard/report creation (Tableau, QuickSight).
• Proficiency in Python (Pandas, NumPy, SciPy, etc.).
• Experience with SQL and data querying.
• Familiarity with AWS data and analytics services (Redshift, Athena, QuickSight, Glue).
• Knowledge of data integration and ETL processes.
• Familiarity with machine learning models and AI frameworks.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication skills to convey complex technical concepts to non-technical stakeholders.
• Ability to work in a collaborative and cross-functional environment.
• Self-motivated with a strong focus on continuous learning and improvement.

BI Development:

• Design and implement interactive dashboards and reports using Tableau and Amazon QuickSight.
• Create data visualizations and reporting tools to enable decision-making for business leaders and stakeholders.
• Ensure high-quality data and performance optimization in BI solutions.

Data Integration & ETL:

• Collaborate with data engineering teams to create efficient data pipelines.
• Integrate data from multiple sources (databases, APIs, cloud platforms) into the BI tools.
• Perform data transformation and cleansing tasks using Python and AWS data services.

AI Integration into BI:

• Work with data scientists and AI teams to embed machine learning models and AI insights into BI dashboards and reports.
• Automate data-driven decision processes using predictive analytics and AI models.

AWS Cloud Infrastructure:

• Leverage AWS services (e.g., S3, Redshift, Glue, Lambda) to build scalable and efficient BI solutions in the cloud.
• Ensure the security, scalability, and performance of BI and AI systems on AWS.

Collaboration & Communication:

• Work closely with business analysts and stakeholders to understand business needs and provide tailored BI solutions.
• Communicate technical insights to non-technical stakeholders effectively.

Continuous Improvement & Optimization:

• Monitor and optimize BI system performance, data quality, and user experience.
• Stay up to date with the latest trends in BI, AI, and AWS to continually improve the solutions provided.