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Marketing Data Architect
Job Title: Marketing Data Architect
Location: Roseland, NJ
ADP, LLC seeks a Marketing Data Architect at our Roseland, NJ location. Responsibilities: Guide the design, development, and maintenance of sales and marketing analytics data architecture for marketing investments. Work with business and technical leaders to present analysis and suggest enhancements to the data and processes that improve marketing decisions and sales processes. Work with internal stakeholders to understand new business needs and gaps in analytics to drive future enhancements of the data warehouse. Define data sources, reports, and Key Performance Indicators (KPIs) across multiple subject areas to analyze sales and marketing processes across various products and channels. Integrate budgeting and attribution tools to ADP's data mart to enhance the company's return on investment (ROI) capabilities. Initiate projects/processes to improve data quality, define data sources, reports, and KPIs across multiple subject areas to analyze processes across different products and channels. Promote the advancement of the company's predictive modeling and machine learning capabilities.
Education and Qualifications/Skills and Competencies:
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science or a related field plus six (6) years of related experience. Employer will accept a master's degree plus three (3) years of experience in lieu of a bachelor's degree plus six years of experience.
Two (2) years of experience must include: Predictive modeling, machine learning, performance tuning, and data warehousing; Sales and marketing tools, including Eloqua, Salesforce, and Google Analytics; Amazon Web Services (AWS); Infrastructure, database architecture, and setup of AWS, including Redshift, S3, EC2, and VPC; Relational databases, including Oracle, SQL Server, DB2, and Netezza; NoSQL Databases, including MongoDB; Building enterprise-wide analytical dashboards and reports in Tableau and Cognos; Big data technologies, including Hadoop, Hive, Spark, Sqoop, and Kafka; Python; and ETL tools, including Informatica, Snaplogic, and Talend.