Data Engineer, Marketing Science – Hearts & Science/Omnicom Media Group

Data Engineer, Marketing Science

The Company: Hearts & Science has been inspired by confident marketers seeking business advantage in a world of personalized digital marketing, where CRM and addressable channels converge, and decisions must be made in real time to aggregate effective reach and deliver the right message at the right time. Designed to inform brand strategies with real-time insights, Hearts & Science is a data-driven marketing agency with expert media planning and buying capabilities, among other services that include shopper marketing, marketing innovation and content activation. Overview Open to locations: Atlanta, Los Angelas, NYC, Chicago, and Dallas, TX This role will be reporting to the Senior Director, Data Engineering and assist in mentoring a team of Data Analysts and Engineers who build, enhance, and optimize ETL (Extract, Transform, Load) jobs, implement data warehouse automated solutions, conduct QA, and manage day-to-day tasks. The Senior Engineer will be responsible for the continued success of existing data warehouse processes, prioritizing new projects as needed, and ensuring tasks are completed per schedule. The candidate must have strong data warehouse, data pipeline design/development, SQL, AWS Cloud and Big Data Technologies experience. You will have the opportunity to contribute to end-to-end platform design for our cloud architecture and work multi-functionally with our Analytics, Data Science, IT and Investment teams to build batch and real-time data solutions. This is a very hands-on position, requiring extensive experience developing workflows in Python, willingness to dive into legacy code repositories and maintaining complex data transformation processes on AWS cloud. Good decision-making, time management, prioritization and escalation skills are traits needed to ensure continued success in this role. Qualifications Bachelors in Computer Science or similar technical degree within a STEM field 2 to 5 years of hands-on experience in building data pipelines using traditional ETL tech stack, platform APIs and big data technologies 2 to 5 years of experience in programming languages including as Python and working within a Linux based environment Experience designing, deploying, and supporting production cloud services in AWS ecosystem including EC2, S3 and Redshift Can speak to concepts and designs/benefits to multiple audiences as well as interpret high level business requirements from conversation Able to work within a cross-functional team environment with people from multiple business units, vendors, countries, and cultures Working experience within the advertising/media industry with knowledge of basic media math Experience in Social Media Datasets such as Twitter, Facebook, Instagram is a plus Experience in Google Campaign Manager, Xandr, or Adobe Analytics datasets is a plus Experience with Google Cloud products is a plus Experience with Microsoft PowerAutomate is a plus Experience using Project Management tools such as Jira is a plus Experience creating data visualizations and using tools such as Tableau is a plus Responsibilities Contribute to the growth of the enterprise data warehouse (EDW) by working alongside stakeholders to produce accurate information within database objects used in reporting, strategic planning and decision making Assist the Senior Director in developing long-term strategies and capacity planning for meeting future data warehouse and data automation needs Meet with end-users and data SMEs to clarify requirements and business rules needed to design, develop, and implement ETL/ELT processes Collaborate with peer Data Engineers to build upon and support our CI/CD pipelines hosted within our extensive GIT repository Mentor our emerging Data Analysts, including providing feedback and suggestions for their planned workflows prior to deployment into production Respond, investigate and correct reported data inaccuracies within the EDW compared to source and business-expected results Establish relationships with external and internal POCs to ensure seamless inbound and outbound Data Delivery expectations are met Implement and support backend maintenance processes that enforce ongoing data optimization and corporate retention policies while ensuring the historical data needs of the client are met Document and maintain all the processes and procedures pertaining to ETL and data warehouse usage/development, contributing to the team knowledgebase when applicable.