Data Engineer II - NBC Sports Next

Company Description

NBC Sports Next is where sports and technology intersect. We’re a subdivision of NBC Sports and home to all NBCUniversal digital applications in sports and technology within our two groups: Youth & Recreational Sports; and Golf. 

At NBC Sports Next, we make playing sports better through innovative technology and immersive experiences for athletes, coaches, players and fans. We equip more than 30MM players, coaches, athletes, sports administrators and fans in 40 countries with more than 25 sports solution products, including SportsEngine, the largest youth sports club, league and team management platform; GolfNow, the leading online tee time marketplace and provider of golf course operations technology; GolfPass the ultimate golf membership that connects golfers to exclusive content, tee time credits, and coaching, tips; TeamUnify, swim team management services; and GoMotion, sports and fitness business software solutions.

At NBC Sports Next we’re fueled by our mission to innovate, create larger-than-life events and connect with sports fans through technology that provides the ultimate in immersive experiences.  

Golf fuses the team behind products and services like GolfNow, TeeOff and GolfPass, which better connects golfers and golf facilities around the world through innovative solutions like cloud-based golf course management and SmartPlay contactless technology and services that create optimum golfing experiences.  

Come join us as we work together as one team to innovate and deliver what’s Next. 

Job Description

GolfNow has an exciting opportunity for an experienced Data Engineer II. In this role as part of the Data Engineering Team, you work to manage the full lifecycle of our data warehousing needs. You will read and write complex queries, demonstrate the ability to create database objects (tables, views, stored procedures, user-defined functions) and create and maintain ETL pipelines. Our data warehouse and data operations are built on top of Microsoft and AWS technologies including MS SQL Server, SSIS, PowerShell, and other AWS cloud technologies. To perform this job successfully, an individual would need to be able to understand complex business processes, gather requirements, work efficiently, and verify their results.

Responsibilities include but are not limited to:

• Work within a small team of passionate data engineers and data scientists.
• Compile user requirements and specifications for reports.
• Contribute to the management of the day-to-day operations of running our Data Warehouse.
• Build, analyze and manage reports and dashboards for business stakeholders.
• Respond to users to troubleshoot and/or improve existing reports.
• Collaborate with internal QA on customer acceptance testing.
• Develop SQL scripts and objects to support reporting functionality and performance.
• Build data pipelines and ETLs for loading source system data into the data warehouse for further reporting and analysis.
• Assist in building scalable data models to support reporting and tracking of key business and product metrics.
• Help identify better practices, tools, and relevant trends that can positively influence the data operations across the business.
• Other duties may be assigned as needed by management.

Qualifications

All candidates must meet the qualifications below: 

• A minimum of 3 years of data engineering experience is required.
• Bachelor’s Degree in Computer Science or related field/relevant industry experience in data engineering.
• Strong experience with SQL Server database and related technologies such as SSIS, SSRS and SSMS
• Advanced knowledge of TSQL tuning
• Experience in the Azure Cloud Environment including ETL processing
• Experience in the AWS Cloud Environment including ETL processing
• Advanced experience and knowledge of T-SQL Microsoft SQL Server Database Platforms.
• Working experience developing and refactoring SQL Stored Procedures.
• Experience using source control with Git or Team Foundation Server.
• Experience with modeling data structures in both transactional and analytical platforms.
• Experience with on