Senior Data Engineer

As a Data Engineer at UPS, your role involves participating in the support of batch and real-time data pipelines for Marketing and Finance business units. You will be responsible for integrating data from various sources, performing ETL data conversions, and facilitating data cleansing and enrichment. Your duties will include full systems life cycle management activities, such as analysis, technical requirements, design, coding, testing, and implementation of systems and applications software. Additionally, you will contribute to synthesizing disparate data sources to support reusable and reproducible data assets. **Key Responsibilities:** - Supervising and supporting data engineering projects, building solutions leveraging software/application development knowledge. - Developing and delivering data engineering documentation. - Gathering requirements, defining scope, and integrating data for data engineering projects. - Recommending analytic reporting products/tools and supporting the adoption of emerging technology. - Performing data engineering maintenance and support. - Providing implementation strategy, executing backup, recovery, and technology solutions for analysis. - Utilizing ETL tool capabilities to pull data from various sources and load transformed data into a database or business intelligence platform. - Coding using programming languages like Python/Spark for statistical analysis and modeling. **Qualifications Required:** - Proficiency in programming languages for statistical modeling, data warehousing, Cloud solutions, and building data pipelines. - Experience in developing notebooks in Data bricks using Python, Spark, and Spark SQL. - Strong understanding of cloud services platforms (e.g., Azure) and data life cycle stages. - Proficiency in using Azure Data Factory and other Azure features like LogicApps. - Knowledge of Delta lake, Lakehouse, and Unity Catalog concepts is preferred. - Understanding of cloud-based data lake systems and data warehousing solutions. - Experience with AGILE concepts for development, including KANBAN and Scrums. - Strong knowledge of data interconnections between operational and business functions. - Understanding of data life cycle stages, data environment scalability, algorithms, data structures, and data optimization. - Proficiency in analytic reporting technologies and environments (e.g., Power BI, Looker, Qlik, etc.). - Ability to guide team members on performing data analysis and presenting findings to stakeholders. - Bachelor's degree in MIS, mathematics, statistics, computer science, or equivalent job experience. UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.,