You should have experience in understanding and translating data, analytic requirements, and functional needs into technical requirements while collaborating with global customers. Your responsibilities will include designing cloud-native data architectures to support scalable, real-time, and batch processing. You will be required to build and maintain data pipelines for large-scale data management in alignment with data strategy and processing standards. Additionally, you will define strategies for data modeling, data integration, and metadata management. Your role will also involve having strong experience in database, data warehouse, and data lake design and architecture. You should be proficient in leveraging cloud platforms such as AWS, Azure, or GCP for data storage, compute, and analytics services. Experience in database programming using various SQL flavors is essential. Moreover, you will need to implement data governance frameworks encompassing data quality, lineage, and cataloging. Collaboration with cross-functional teams, including business analysts, data engineers, and DevOps teams, will be a key aspect of this role. Familiarity with the Big Data ecosystem, whether on-premises (Hortonworks/MapR) or in the Cloud, is required. You should be able to evaluate emerging cloud technologies and suggest enhancements to the data architecture. Proficiency in any orchestration tool like Airflow or Oozie for scheduling pipelines is preferred. Hands-on experience in utilizing tools such as Spark Streaming, Kafka, Databricks, and Snowflake is necessary. You should be adept at working in an Agile/Scrum development process and optimizing data systems for cost efficiency, performance, and scalability.,