Data Engineer

Omnicom Media US H&S•Chicago, IL

5h•Hybrid

About The Position

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. This role will be reporting to the Senior Director, Data Engineering and be part of Data Engineering Team who build, enhance and optimize ETL (Extract, Transform, Load) jobs, implement automated data warehouse solutions, conduct QA and manage day-to-day tasks. The candidate must have strong data warehouse, data pipeline design/development, SQL, AWS Cloud and Big Data Technologies experience. As an experienced Data Engineer, you will also provide support and mentor other team members who will look for your experience and guidance to solve a problem. Complete oversight of our data warehouse and the ability to work directly with stakeholders on Investment, Strategy and Analytical teams are additional tasks that will be expected of you. 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 maintain 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.

Requirements

Bachelor’s in Computer Science or similar technical degree within a STEM field
5+ years of hands-on experience in building data pipelines using traditional ETL tech stack, platform APIs and big data technologies
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

Nice To Haves

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