Intern, Data Solutions

Job Description

As an Intern- Data Solutions , you will be part of the Commercial Data Solutions team, providing technical/data expertise development of analytical data products to enable data science & analytics use cases. In this role, you will create and maintain data assets/domains used in the commercial/marketing analytics space - to develop best-in-class data pipelines and products, working closely with data product owners to translate data product requirements and user stories into development activities throughout all phases of design, planning, execution, testing, deployment and delivery. Your specific responsibilities will include: Hands-on development of last-mile data products using the most up-to-date technologies and software / data / DevOps engineering practices Enable data science & analytics teams to drive data modeling and feature engineering activities aligned with business questions and utilizing datasets in an optimal way Develop deep domain expertise and business acumen to ensure that all specificalities and pitfalls of data sources are accounted for Build data products based on automated data models, aligned with use case requirements, and advise data scientists, analysts and visualization developers on how to use these data models Develop analytical data products for reusability, governance and compliance by design Align with organization strategy and implement semantic layer for analytics data products Support data stewards and other engineers in maintaining data catalogs, data quality measures and governance frameworks Education: B.Tech / B.S., M.Tech / M.S. or PhD in Engineering, Computer Science, Engineering, Pharmaceuticals, Healthcare, Data Science, Business, or related field Required experience: High proficiency in SQL, Python and AWS Good understanding and comprehension of the requirements provided by Data Product Owner and Lead Analytics Engineer Understanding in creating / adopting data models to meet requirements from Marketing, Data Science, Visualization stakeholders Experience with including feature engineering Hands on with cloud-based (AWS / GCP / Azure) data management platforms and typical storage/compute services (Databricks, Snowflake, Redshift, etc) Hands on with modern data stack tools such as Matillion, Starburst, ThoughtSpot and low-code tools (eg Dataiku) Excellent interpersonal and communication skills, with the ability to quickly establish productive working relationships with a variety of stakeholders