Data Engineer

Role Responsibilities: Design, code, test, debug, and document technology solutions for complex projects and programs. Review and analyze large-scale technology solutions to align with tactical and strategic business objectives, as well as enterprise technological environments. Evaluate and develop companywide best practices for engineering and technology solutions, ensuring alignment with industry standards and new technologies. Collaborate with key technical experts and senior technology teams to resolve complex technical challenges and meet project goals. Contribute to the development of Data Mesh capabilities to improve data accessibility across disparate platforms such as Hadoop, Teradata, and SQL Servers. Support Data Science functions by preparing pre-work required for data exploration and analysis. Support System Testing, User Acceptance Testing (UAT), and end-to-end testing activities; develop test automation for batch processes and APIs within a CI/CD environment. Work with Agile methodologies, writing user stories, and participating in Agile ceremonies. Required Qualifications: Extensive experience designing and delivering data solutions in Google Cloud Platform (GCP), leveraging services such as DataProc, DataFlow, BigQuery, and other GCP tools. Expertise in Big Data platforms (e.g., MapR, Cloudera) using technologies like HDFS, Spark, PySpark, and Hive. Proficiency in event-driven solutions using Java, REST APIs, Apache Flink, and Kafka technologies. Experience with relational and NoSQL databases, including MongoDB, SQL Server, Atlas, and Azure SQL. Strong familiarity with wire formats such as XML, JSON, Avro, and CSV, along with serialization/deserialization techniques. Knowledge of security protocols (e.g., Kerberos, JWT) and their integration into data platforms and solutions. Solid understanding of Agile methodologies, including writing user stories and participating in ceremonies such as sprint planning and retrospectives. MUST HAVE - Java API skills #J-18808-Ljbffr