Data Engineer: Build Scalable Pipelines for Analytics

Role & Responsibilities Design, develop, and maintain scalable data pipelines and architectures to support analytical and operational processes. Collaborate with data analysts and scientists to implement data solutions that enable advanced analytics and reporting. Optimize data flows and queries for high performance and efficiency across cloud and on-premise environments. Build and manage data models, data sets, and repositories ensuring data integrity and security. Implement ETL processes using modern tools and frameworks to automate data ingestion and transformation. Monitor system performance, troubleshoot issues, and implement improvements to enhance reliability. Skills & Qualifications Must-Have Skills Proficiency in Python and SQL Experience with Spark, Kafka, and other big data technologies Hands-on experience with cloud platforms, preferably AWS Strong understanding of ETL pipeline development and data warehousing concepts Excellent problem-solving and communication skills Preferred Skills Knowledge of data governance and security practices Experience with containerization tools like Docker or Kubernetes Familiarity with machine learning data workflows Benefits & Culture Highlights Opportunity to work with cutting-edge data technologies in a collaborative environment Supportive culture fostering innovation and continuous learning Competitive compensation and benefits package #J-18808-Ljbffr