Data Engineer II

Responsibilities Design, develop, and maintain scalable ELT/ETL pipelines using Databricks, Apache Spark, SQL, and Python. Build and maintain reliable, high-quality datasets that support enterprise analytics, operational reporting, and AI use cases. Develop data transformations using Delta Lake and Lakehouse architecture best practices. Integrate data from enterprise applications, APIs, databases, files, and other internal and external sources. Collaborate with business stakeholders, analysts, and product teams to understand data requirements and deliver scalable solutions. Monitor, troubleshoot, and optimize production data pipelines for reliability, scalability, and performance. Participate in migrating and modernizing legacy data processes to cloud-native architectures. Improve data quality through validation, testing, monitoring, and automation. Contribute to engineering best practices through code reviews, documentation, and knowledge sharing. Support continuous improvement of the enterprise data platform by identifying opportunities for automation, optimization, and simplification. Requirements Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience. 3+ years of experience in Data Engineering or a related technical role. Strong SQL development skills. Strong Python programming experience. Experience building data pipelines using Apache Spark and Databricks (or similar distributed data processing platforms). Experience developing modern ETL/ELT pipelines. Understanding of data modeling and data warehousing concepts. Experience working with cloud-based data platforms, preferably AWS. Familiarity with Delta Lake or similar modern data storage technologies. Experience using Git and collaborative software development practices. Strong analytical, troubleshooting, and problem-solving skills. Excellent communication and collaboration skills. Core Competencies Proficient in designing and developing scalable ELT/ETL pipelines using Databricks, Apache Spark, SQL, and Python, with a strong focus on data quality and optimization. Experienced in collaborating with stakeholders to deliver data solutions that support enterprise analytics and operational reporting. #J-18808-Ljbffr