Data Engineer (Hybrid)

Job Title 

Job Description

For more than 80 years, Kaplan has been a trailblazer in education and professional advancement. We are a global company at the intersection of education and technology, focused on collaboration, innovation, and creativity to deliver a best in class educational experience and make Kaplan a great place to work.

Our offices in India opened in Bengaluru in 2018. Since then, our team has fueled growth and innovation across the organization, impacting students worldwide. We are eager to grow and expand with skilled professionals like you who use their talent to build solutions, enable effective learning, and improve students’ lives.

The future of education is here and we are eager to work alongside those who want to make a positive impact and inspire change in the world around them.

The Data Engineer at Kaplan North America (KNA) within the Analytics division will work with world class psychometricians, data scientists and business analysts to forever change the face of education. This role is a hands-on technical expert who will help implement an Enterprise Data Warehouse powered by AWS RA3 as a key feature of our Lake House architecture. 

The perfect candidate possesses strong technical knowledge in data engineering, data observability, Infrastructure automation, data ops methodology, systems architecture, and development. You should be expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. You should be able to work with business customers in a fast-paced environment understanding the business requirements and implementing data & reporting solutions. Above all you should be passionate about working with big data and someone who loves to bring datasets together to answer business questions and drive change

Responsibilities:

• You design, implement, and deploy data solutions. You solve difficult problems generating positive feedback.

• Build different types of data warehousing layers based on specific use cases

• Lead the design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work

• Build scalable data infrastructure and understand distributed systems concepts from a data storage and compute perspective

• Utilize expertise in SQL and have a strong understanding of ETL and data modeling

• Ensure the accuracy and availability of data to customers and understand how technical decisions can impact their business’s analytics and reporting

• Be proficient in at least one scripting/programming language to handle …