Posted:1 month ago|
Platform:
Work from Office
Full Time
Duration: 12 Months Work Type: Onsite Job Description: The Marketing Engineering organization in Strategy, Planning & Operations is looking for a Data Engineer eager to provide the engineering muscle for core engineering work around data architecture, data pipeline development, and deploying production workflows to continue improving our data & reporting needs for Marketing in an AI future. You will be responsible for: Working with a technical leader to lead major engineering initiatives to support decision-making by the business You will help manage production data workflows, ensuring timely updates are made through a standard SDLC process. You will help design and develop new architectures and workflows to support the growing business needs of the client'sMarketing. Who You'll Work With You will report to a manager within Advanced Analytics and work directly with a Team Leader in the Engineering Center of Excellence You will work closely with Modelers, Business Stakeholders, Analytics Translators as well as IT Who you are: You like working with Data and love getting the business to adopt Data Insights. Minimum qualifications are: Experience with data modeling, data warehousing, and building ETL pipelines Experience in SQL, Python, and Unix/Bash scripting Experience working with Docker, Git, and various cloud platforms like Google Cloud and Azure. Writing complex, optimized SQL queries across large data sets Experience in communicating complex technical concepts to a broad variety of audiences Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy. Preferred Qualifications: BS/MS in Computer Science/Engineering. 4-7 years of experience in a Data Engineering or similar role Knowledge of software engineering standard methodologies across development lifecycles including agile methodologies, coding standards, code reviews, source management, build processes, testing and operations.
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