Data Engineer

Overview As a Data Engineer for our Digital Services division, you will drive the evolution of our next generation data infrastructure, which powers a wide range of analytics and software products. You will be responsible for designing, developing, and maintaining advanced data pipelines using the latest technologies in cloud computing and data processing. In this pivotal role, you will collaborate with cross-functional teams including data scientists, software engineers, and business analysts. You will interface with non-technical stakeholders to ensure that their needs are met in the form of functional and non-functional requirements. Responsibilities Design, build, and maintain our data infrastructure to support analytics and integration into software products and services. Partner with data scientists to build processing pipelines that enable them to rapidly create high-quality machine learning models. Work with software engineers to develop and maintain pipelines to feed data to our growing software portfolio. Manage ETL/ELT processes as code and foster a codebase that is extensible and maintainable by all team members. Manage the transition from quick prototype to full scalable solution that supports production products. Identify, recommend, and implement innovative approaches and technologies that will evolve our existing processes Provide ad hoc support to the engineering team, including POC software development, ML model development, and data analysis, as project needs arise. Qualifications Education and experience BS/MS Degree in Computer Science, Engineering, Data Analytics, or related field. 3+ years’ experience in data engineering, ETL development, or similar role. Strong problem-solving skills to discover, address, and resolve issues. Demonstrated ability to translate technical concepts into actionable insights for different stakeholders. Language and Technical Skills Proficient in programming languages such as Python and SQL and development tools such as Git. Experience with cloud platforms such as Azure, AWS, or GCP for deploying and managing data infrastructure. Skilled with rational database schema design. Hands-on experience with data processing tools and platforms such as Snowflake, Azure Synapse, Azure Data Factory, Databricks, etc. Solid understanding of machine learning models, tools, libraries, and approaches. Experience with business intelligence tools such as Power BI, Spotfire, Cognos, Tableau, Qlik. Physical Demands and Work Environment Work is usually performed in an office environment with normal noise levels. Involves prolonged sitting and computer usage. Work may involve limited travel. #J-18808-Ljbffr