IMDb is the world's most popular and authoritative source for movie, TV, and celebrity content. The IMDb consumer site (www.imdb.com) is the #1 movie website in the world with a combined web and mobile audience of more than 250 million unique monthly visitors. IMDb offers a searchable database of more than 250 million data items including more than 5 million movies, TV, and entertainment programs and more than 8 million cast and crew members. We have a vast data set, tons of passionate customers, and are constantly improving the experience on our site and apps.
As a data engineering leader at IMDb, we look to you for design, implementation, and successful delivery of large-scale, critical, or difficult data solutions involving a significant amount of work. These efforts are both new data solutions and refactoring existing. You heavily influence the design and write a significant portion of the “critical-path” code, but you think in terms of architecture, not just code. Where needed, you integrate your team’s data solutions with those owned by other teams. You influence your team’s technical and business strategy by making insightful contributions to team priorities and overall data approach. You take the lead in identifying and solving ambiguous problems, architecture deficiencies, or areas where your team bottlenecks the innovations of other teams. You make data solutions simpler.
Bachelor's degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering)
3+ years of relevant experience in one of the following areas: Data engineering, database engineering, business intelligence or business analytics
3+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets
Demonstrable experience in scripting languages (Python, Perl, Ruby) and Excel
Demonstrated strength in data modeling, ETL development, and Data warehousing
Experience with Tableau, Matillion, and AWS services (Redshift, S3, AWS Glue, EMR, DynamoDB)
Knowledge of distributed systems as it pertains to data storage and computing
Passionate about the entertainment industry
Works well individually or in a team, driving things forward even in the face of ambiguity and imperfect data
Master’s degree in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering)
Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
Experience working with other engineers in defining data engineering best practices and leveraging software development lifecycle best practices such as agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations