Senior Data Analyst, ITC

WHO YOU’LL WORK WITH The Senior Data Analyst will work with the Data and Artificial Intelligence team at Nike. Data and Artificial Intelligence team at Nike drives the enterprise-wide data needs that fuels Nike's innovation. This role is crucial in translating the business needs of Nike into data requirements and thereby have a significant impact on the growth of Nike's business. This role will fuel the foundational data layers that'll power the advanced data analytics of Nike. WHO WE ARE LOOKING FOR We are looking for individuals who are highly driven and have the ability to understand and translate business requirements into data needs. The candidates should be good at problem solving and have in-depth technical knowledge on SQL, bigdata with optional expertise in pyspark. They need to have excellent verbal and written communication and should be willing to work with business consumers to understand their needs and requirements. Role requirements include

• A minimum of bachelor’s degree in computer science/information science engineering
• 5+ years of experience in data and analytics space with hands-on experience
• Very high expertise in SQL with the ability to work on platforms like databricks, hive and snowflake
• Ability to integrate and communicate moderately complex information, sometimes to audiences who are not familiar with the subject matter. Acts as a resource to teammates.
• Ability to integrate complex datasets and derive business value out of data
• Independently utilizes knowledge, skills, and abilities to identify areas of opportunity, resolve complex problems & navigate solutions.

WHAT YOU’LL WORK ON In this role you'll be working with a team of talented data engineers, product managers and data consumers who'll focus on the enterprise-wide data needs of Nike. You'll have a direct impact on the deliverables of the team, and you'll be guiding the team on solving complex business problems. Some of your day-to-day activities will include -

• Collaborating with engineers, product managers and business users for optimal usage of data
• Understanding business used cases using data
• Analysing data to inform business decisions
• Troubleshooting complex data integration problems at a business level
• Writing and enhancing complex queries in databricks, hive, snowflake
• Providing inputs to the product management in growing the data foundational layers

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