Data Engineering Intern - McKinsey Global Institute (MGI)

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), Microsoft-Excel, PowerBI, Python Programming, R Programming, Snowflake, SPARK Programming, SQL, Tableau

Job Description

WHO YOU'LL WORK WITH

You will be based in our Costa Rica office work with the Economics Team that is part of the McKinsey Global Institute (MGI). MGI is the business and economics research arm of McKinsey & Co. and combines the disciplines of economics and management, employing the analytical tools of economics with the insights of business leaders.

The role is intended to support MGI’s data asset development initiatives, a core part of client impact mission of the team. The ideal candidate will be detail-oriented, have great organizational skills, be service-oriented and passionate for data ops topics.

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 a variety of projects to support the growth of MGI’s data asset portfolio. You will join a global team of economists and will support different team experts in the development of new tools and/or the maintenance of current proprietary databases, especially through structuring and managing databases, developing data workflows and processes, and building visualizations and dashboards.

Some of your responsibilities would include to assist in designing, building, and maintaining data pipelines that extract, transform, and load (ETL) data from various sources into our data ecosystem, understand the objectives and priorities of data asset portfolio expansion, develop efficient and scalable data processing solutions that meet business requirements.

Also you will participate in data quality assessment and validation processes to ensure accuracy, consistency, and reliability of data assets, collaborate with cross-functional teams, including data analysts and leaders to understand data consumption needs and optimize data delivery and will contribute to the documentation of data engineering processes, including pipeline architecture, data flow, and transformation logic.

You will assist in troubleshooting and resolving data pipeline issues to ensure smooth and uninterrupted data operations and support ad-hoc data requests and assist in data-related projects as needed.

QUALIFICATIONS

• Final year of bachelor’s or master’s degree in Data Engineering, Data Science or Data Analytics
• Passion for data ops topics
• Strong analytical and problem solving skills
• Proficiency in Python, Snowflake, Tableau and Excel required 
• Experience / Exposure to SQL, R, Knime, Alterix or Databricks and with data visualization tools (e.g. Tableau, Power BI, Domo) is a plus
• Self-motivated, proactive, and able to work both independently and collaborative
• Attention to detail
• Excellent communication and interpersonal skills