Data Engineer Level 4

This role is responsible for maintenance, support and daily operations of the Media & Growth Marketing (MGM) modeling and analytics software applications. This role will ensure daily that MGM model data flows and dashboard extracts are executing and up to date. The Data Engineer is responsible for diagnosing and resolving application issues to ensure optimal performance and usability for downstream MGM system users., Monitor and maintain operational readiness and reliability of the MGM machine learning and ETL operational systems Develop automated processes and technical documentation Partner with platform vendors, in-house support teams, Marketing partners, and other stakeholders to coordinate issue resolution and maintain strong working relationships. Assess, prioritize, and manage reported issues based on business impact, operational urgency, and alignment with MGM and departmental partner needs. Communicate expected resolution timelines, progress updates, and closure status to ensure stakeholders remain informed throughout the support process. Evaluate and improve the team’s data ETL process for modeling by: Reviewing current workflows, dependencies, and pain points Identifying opportunities to streamline, standardize, and centralize data movement Developing a more scalable, reliable process that supports modeling and downstream analytics needs Relevant Skills

Demonstrate expert data engineering skills supporting workflow automation using tools such as Apache Airflow, Databricks, or Azure Data Factory or ML platforms such as Dataiku or DataRobot. Familiarity leveraging ML algorithms such as Decision Trees, Logistic Regression, Random Forest and XGBoost using an ML platform and/or an IDE such as Spyder or PyCharm. Working knowledge of Tableau Desktop/Server. Ability to research, analyze and resolve operational issues such as run-time failures, long-running job execution and/or platform errors in a timely manner. Provide Root Cause analyses (RCA) to identify and proactively prevent future issues. Expert experience working with large volumes of data to include integration and cleansing. Knowledge of production support concepts such incident reporting, testing, debugging, monitoring, and audits. Skill in creating and maintaining technical documentation to include run book creation for routine or repeatable operations, code annotation, and other asset documentation. Strong knowledge of SQL, and Python (3+ years). Snowflake SQL experience preferred., Understanding and exposure to data science and Machine learning/random forest modeling etc. Ability to develop effective working relationships Possessing excellent interpersonal skills to include teamwork, facilitation, and negotiation Ability to work independently or as part of a team to resolve issues Effective written and verbal communication skills Demonstrate an ability to work under pressure, manage competing priorities and meet or exceed expectations regarding issue identification, resolutions and communication

Jones Lang LaSalle

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