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This role requires strong technical expertise, excellent communication skills, and the ability to collaborate effectively across teams.\n\nResponsibilities: \nDevelop and optimize scalable data pipelines (batch and real-time) and ETL processes using Python, PySpark, SQL, and Databricks.\nImplement and manage data solutions on at least one cloud platform (Azure, AWS, or GCP).\nApply DevOps practices to ensure efficient CI/CD, monitoring, and automation of data workflows.\nDesign and deliver insightful dashboards and reports using a data visualization tool (e. g., Power BI, Tableau, Looker).\nPartner with stakeholders to translate business requirements into technical solutions.\nEnsure data quality, governance, and security standards are consistently met.\nCommunicate technical concepts clearly to both technical and non-technical audiences.\nContribute to innovation initiatives, including projects involving generative AI (Gen AI).\n\nRequirements: \nBachelor's or master's degree in computer science, information systems, or a related field.\n2-6 years of professional experience in data engineering.\nStrong proficiency in Python, PySpark, SQL, and Databricks.\nHands-on experience with at least one cloud platform (Azure, AWS, or GCP).\nWorking knowledge of DevOps tools and practices (CI/CD pipelines, version control, automation).\nExperience with at least one data visualization tool (Power BI, Tableau, Looker, etc. ).\nExcellent verbal and written communication skills.\nPreferred: Exposure to generative AI technologies.\n\nDesired Attributes: \nStrong analytical and problem-solving skills.\nAbility to work independently while contributing to team success.\nPassion for continuous learning and adopting emerging technologies.\nSkills\nDatabricks, PySpark, 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