The Data Engineer is responsible for the continued development and optimization of the company’s Data Lake and/or Customer Data Platform (CDP) to support data driven decision making within Marketing. He/She leads the collection, cleaning, and transformation of data from multiple channels into the Data Lake and/or Customer Data Platform in support of the segmentation, analytics, reporting, and activation needs of marketers. This individual is responsible for cultivating new data sources and synthesizing them into the current data lake, enhancing the identity graph as they relate this data. This position is responsible for bringing the strategy and roadmap to life through data engineering and data activation processes, and oversees the delivery of high quality data to marketing stakeholders and data scientists. This individual interacts regularly with IT on development of new ETL (Extract, Transform, and Load) jobs, maintenance, and troubleshooting. The Data Engineer also provides key input in support of the overall marketing data architecture. In addition, the individual ensures that quality performance data is captured and tools are developed to support performance reporting and audience insights mining.
Responsibilities and Duties
- Designs and develops Extract, Transform, and Load (ETL) processes within Customer Data Platform in support of the segmentation, analytics, and reporting needs of the business
- Develops processes to clean and transform data into the processed data store within the Customer Data Platform and build aggregated views in the analytical data store in support of reporting and business intelligence needs of Marketing stakeholders
- Develops automated quality assurance processes to monitor quality of inbound data and ensure the continued accuracy of data processing within the platform
- Develops and manages data processing jobs to assign customers to marketing segments in the Customer Data Platform using demographic data, behavioral data, and intent signals and works with data scientists to incorporate machine learning outcomes into the overall customer segmentation model
- Plays a significant role as a contributor to projects involving marketing stakeholders, software vendors, IT, and data owners to specify and execute new data feeds into the Customer Data Platform and/or Data Lake from internal repositories and marketing applications (web analytics, data warehouse, etc.)
- Supports the Data Engineering Manager in creating reporting and data visualization dashboards.
Knowledge and Skills
- Strong coding skills in SQL, Spark, R and Python
- Strong technical knowledge of Hadoop and Spark ecosystem, including Hive, Sqoop, and Oozie
- Strong knowledge of data modeling principles and best practices in building analytics repositories in SQL and NoSQL environments
- Experience with cloud computing in the Azure environment with Databricks and Data Factory, or similar technologies
- Ability to diagnose and troubleshoot complex data quality issues
- Ability to translate marketing stakeholder requirements into technical specifications
- Experience building and managing data pipelines and repositories in cloud environments such as Microsoft Azure
- Experience in dashboard development (Power BI, Tableau)
- Experience with Intermediate Operating System Fundamentals, Agile Development, SQL & PL/SQL, Database Administration, Data Security and Data Analytics
- Familiarity with documentation skills, attention to detail and organization
- Excellent written and verbal communication skills
- Bachelor's degree in Computer Science or related discipline or the equivalent in eiducation and experience.
UPS is an equal opportunity employer. UPS does not discriminate on the basis of race/color/religion/sex/national origin/veteran/disability/age/sexual orientation/gender identity or any other characteristic protected by law