Data Engineer

Agency:

Job Function:

Job Subfunction:

Job Description:

Role Overview

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 data warehouse data pipeline design/development SQL AWS Cloud and Big Data Technologies experience. As a Data Engineer 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.

Key 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

Qualifications

Education & Technical Experience Requirements

• Bachelors in Computer Science or similar technical degree within a STEM field
• 3 years of hands-on experience in building data pipelines using traditional ETL tech stack platform APIs and big data technologies
• 3 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

Omnicoms policy requires employees to work in the office for a minimum of three days a week unless additional in-office days are directed by their agency or manager. Our objective is to increase this requirement over time and many of our agencies as well as Omnicoms corporate group already require five days of in-office attendance.

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