The Data Engineer plays a crucial role in driving actionable insights that support business strategies. They manage and develop data pipelines, partnering closely with stakeholders to address technical issues and ensure operational efficiency within Business Intelligence and data teams. Collaborating with data and analytics experts, they optimize data systems, analyze and enhance organizational data footprints, and contribute to data quality initiatives.

• Develop and manage data pipelines to support business strategies through actionable insights into business performance, operational efficiency, and other key business performance metrics
• Partner with business stakeholders to assist with data-related technical issues and support Business Intelligence and data teams operational requirements
• Work with data and analytics experts to strive for greater functionality, traceability and cross functional cohesion in our data systems
• Analyze, understand and optimize the data footprints of our organization
• Assist the development and architecture teams on data quality and various Proof of Concept (POC) initiatives

• Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field and 4 years' experience working with enterprise technology in Azure and Databricks
• Working knowledge of designing, building, and optimizing big data data pipelines, and data sets in ADF
• Working SQL knowledge and experience with relational databases, query authoring (SQL)
• Working knowledge performing root cause analysis on internal and external data processing related issues
• Understanding processes supporting data transformation, data structures, metadata, dependency, and workload management
• Knowledge with big data tools: Hadoop, Spark. Knowledge of relational SQL and NoSQL databases
• Knowledge of object-oriented/object function scripting languages: Python, Java, etc.