Business Intelligence Engineer
New York, NY
Data Science & Business Intelligence
LADDERS is a fast paced, high growth internet company focused on building data driven web and mobile web products that connect job seekers and employers. We're based in Manhattan, and we're dedicated to developing better products that help people manage market, and move-up in their careers, and helping employers find and hire their next reliable professional.
We are looking for a talented Business Intelligence Engineer to join our Business Intelligence team. The Business Intelligence Engineer will participate in business analytics, providing ad-hoc and automated reporting, data modeling and data visualization. In this highly visible position, you will work with various team members from different departments including Data Science, Marketing, Product, and Engineering. In order to succeed, you will need to be comfortable juggling several projects at once and with the occasional quick turn around. You will play a central role to help business make data driven decisions.
Responsibilities of the BI Engineer:
- Interact with Business to gather requirements, prepare technical and functional specifications
- Design and build analytics and reporting solutions for production and business
- Design, develop, and maintain reports, dashboards, and self-service BI tools for business users
- Maintain high availability of data warehouse and reporting infrastructure
Qualifications of the BI Engineer:
- BS or MS in a quantitative field
- 2+ years of experience with SQL development and relational databases (e.g., MS SQL Server, Oracle, Postgres, Redshift)
- 2+ years of experience developing analytics solutions (reports, dashboards, data models)
- Proficiency in planning and management of scope of work and time estimation
- Strong verbal and written communication skills
Preferred Qualifications of the BI Engineer:
- Experience with Business Intelligence and reporting automation tools (e.g. Tableau, SSIS)
- Experience with building/deploying complex ETL pipelines.
- Proficiency with predictive analytics, statistical modeling, data visualization and machine learning.