Business Intelligence Data Engineer

LEGENDS

Founded in 2008, Legends’ operating divisions worldwide include – Global Partnerships, Global Sales, Collegiate, Hospitality, Global Merchandise and Attractions – offering clients and partners a 360-degree data and analytics fueled service solution platform to elevate their brand and execute their vision. Currently, Legends works with marquee clients across business verticals including professional sports; collegiate; attractions; entertainment; and conventions and leisure. We are the industry leaders in designing, planning, and realizing exceptional experiences in sports and entertainment. For more information, visit www.Legends.net and follow us on Twitter and Instagram @TheLegendsWay.

THE ROLE

As a Data Engineer, you will be responsible for developing and maintaining data pipelines, optimizing data flow, and supporting the integration of new datasets into our BI environment. The ideal candidate will have hands-on experience with Python, Databricks, and a strong background in working with large datasets. Familiarity with Lakehouse structures and the ability to schedule, monitor, and troubleshoot data loads will be key to success in this role.

ESSENTIAL FUNCTIONS

• Implement logic to ingest and cleanse new datasets, ensuring they meet BI requirements and standards.
• Utilize Python notebooks within Databricks to analyze and process large datasets, adhering to BI standards and data quality requirements.
• Collaborate with cross-functional teams to understand data requirements and design robust data pipelines.
• Develop and maintain ETL processes to ensure the efficient flow of data from various sources to our BI environment.
• Schedule, monitor, and troubleshoot data loads to ensure timely and accurate delivery of data.
• Work closely with the Business Intelligence team to understand data needs and provide support for BI initiatives.
• Ensure the security, reliability, and compliance of data in accordance with regulatory requirements and internal policies.
• Collaborate with stakeholders to optimize data and support the adoption of Lakehouse architecture.

QUALIFICATIONS

To perform this job successfully, the candidate must be able to perform each essential duty above at the highest levels. The requirements listed below are representative of the knowledge, skill, and/or ability required.

• Bachelor’s degree in computer science, Information Systems, or a related field.
• Minimum three years of experience in Data Engineering, with a focus on large datasets and ETL processes.
• Strong proficiency in Python and experience with Databricks.
• Experience with scheduling, monitoring, and troubleshooting data loads.
• Solid understanding of data warehousing concepts and BI environments.
• Excellent problem-solving skills and attention to detail.
• Strong project management skills, capable of overseeing complex data engineering projects.
• Excellent communication and interpersonal skills for effective collaboration with cross-functional teams.
• Experience with Microsoft platforms, including Dataverse, CRM, and F&O, to enhance data integration and support business processes.
• Experience supporting front-end dashboard reporting, collaborating with other business intelligence team members to assess and optimize dataset usage for effective insights.

DESIRED EXPERIENCE

• Familiarity with Lakehouse structures.
• Advanced degree in a relevant field.
• Experience with cloud-based data solutions (e.g., Azure, AWS).
• Knowledge of data security and compliance in data engineering environments.
• Exposure to advanced data analytics and machine learning concepts.
• Knowledge of Power BI and Power Query basics is recommended.

COMPENSATION

Competitive salary, commensurate with experience, and a generous benefits package that includes: medical, dental, vision, life and disability insurance, paid vacation, and 401k plan.

WORKING CONDITIONS

Legends is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, disability, or genetic information.