Senior Data Engineer

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow’s ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries. • • • • • • NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future • • • Data Engineer IV Remote Long term Contract Responsibilities: ● Develop and optimize real-time data pipelines from existing data sources. ● Structure and organize large datasets for fast, smooth operations. ● Build and maintain data tables supporting multiple marketing signals across millions of advertisers. ● Collaborate with team members and act quickly on feedback. ● Serve as the data expert for marketing science initiatives. Must-Have Skills: • Ability to build data pipelines and infrastructure from existing data sources. • Experience creatively finding ways to structure data so it runs faster and smoother. • Strong soft skills: partnerships and ability to act quickly on feedback. • Proficiency in Python and SQL (Python preferred). Nice-to-have Skills: • Experience working with large volumes of data. • Familiarity with customer lifecycle management and CRM data. • Marketing expertise, especially with data tables used to power marketing campaigns. Requirements: ● Proven experience building data pipelines and infrastructure. ● Strong skills in Python (preferred) and SQL. ● Ability to creatively structure data for performance and scalability. ● Experience working with large volumes of data (millions of rows). ● Bachelor’s degree in Computer Science, Data Analytics, or related field. ● Strong collaboration and communication skills. ● Experience with customer lifecycle management, CRM data, or marketing data tables is a plus. ● Comfortable working in fast-paced environments with large datasets.