Data Engineer Intern

Key Skills

Analytical and Problem solving, Apache Hadoop, Apache Kafka, AWS, Azure, Big Data Technology, Data Analytics, Data science techniques, Data structuring, Data Warehousing, Database, Effective communication skills, ETL frameworks, Google Cloud Platform (GCP), PowerBI, Python Programming, R Programming, Snowflake, SPARK Programming, SQL, Tableau

Job Description

WHO YOU'LL WORK WITH

You will be based in our San Jose, Costa Rica office as part of McKinsey’s Global Client Capabilities Network (CCN). Colleagues in our global Client Capabilities Network deliver distinctive client impact through assets and expertise and are driven by a culture of innovation.

You’ll be part of the US&CA Regional Research Team. The team is a ~30-person team based in San Jose, Costa Rica, and Waltham, MA, and supports McKinsey consultants and clients on a wide variety of topics that require US & Canada local market knowledge (e.g., demographics, US business environment, regulations, etc.) and has a portfolio of assets and capabilities that are being deployed directly with clients.

This internship position is a 12-month full-time opportunity for students or new professionals looking to gain that extra step towards their professional development.Please note:This internship cannot be used to satisfy the requirements of the Professional Practice.

WHAT YOU'LL DO

You will assist in various projects to support the growth of the US&CA data asset portfolio. You will support different team experts in the development of new tools and/or the maintenance of current proprietary databases, primarily through structuring and managing databases, developing data workflows and processes, and building visualizations and dashboards.

One of your core responsibilities will be building data assets using R, Python and BI tools, including Tableau, PowerBI, and Domo, etc, to generate new insights using data.

You may be asked to facilitate ingestion of large data through online and offline sources, and track and analyze the raw usage metrics of our asset portfolio. You will mine this data to help us better understand user behaviors, proposing changes (“interventions”) to improve product adoption and satisfaction.

QUALIFICATIONS

• Last year pursuing a degree related to Data Engineering, Computer Science, Information Technology, Data Science or Data Analytics
• Strong foundational knowledge of databases, data structures, and SQL
• Familiarity with programming languages such as R and Python, Java, or Scala
• Basic understanding of data warehousing concepts and ETL processes
• Good problem-solving skills and attention to detail
• Excellent communication and teamwork abilities
• A willingness to learn and a proactive attitude toward professional development
• Experience with cloud platforms like Snowflake, AWS, Azure, or GCP is a plus
• Exposure to big data technologies such as Hadoop, Spark, or Kafka is a plus