Lead AWS Data Engineer

As a Lead Data Engineer with 7+ years of experience, your role will involve the following responsibilities: - Multi-year work experience as a Platform Lead, Delivery Leader, or similar role. - Good working knowledge of AWS services, Python, PySpark, and data modeling. - Familiarity with columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data. - Proficiency in ETL, data mining, data warehousing, and segmentation techniques. - Knowledge of databases such as Azure SQL, MSQL, data lakes like Azure Data Lake/Delta lakes, processing tools like Databricks/HDInsight, and BI and reporting tools such as Power BI, Tableau, or similar technologies. - Experience in advanced data management, data processing, and data science-related exploration to derive insights for business decision-making. - Working knowledge of modern infrastructure automation technology stacks and the ability to choose the best tool for each task. - Understanding of various Agile principles, methodologies, and frameworks, particularly those scaled for enterprise-level operations. - Willingness to facilitate knowledge transfer, coach others, and support their learning. - Strong analytical skills, quick grasp, and proactive approach to independent work. - Demonstrated ability to think creatively and analytically in problem-solving scenarios. - Excellent written and verbal communication skills, with the capability to explain new ideas and concepts to both technical and non-technical audiences. - Effective communication with customers, ensuring clarity and transparency. - Eagerness for self-directed learning, with a commitment to continuously enhance skills and knowledge. Please note that the job description does not include any additional details about the company. As a Lead Data Engineer with 7+ years of experience, your role will involve the following responsibilities: - Multi-year work experience as a Platform Lead, Delivery Leader, or similar role. - Good working knowledge of AWS services, Python, PySpark, and data modeling. - Familiarity with columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data. - Proficiency in ETL, data mining, data warehousing, and segmentation techniques. - Knowledge of databases such as Azure SQL, MSQL, data lakes like Azure Data Lake/Delta lakes, processing tools like Databricks/HDInsight, and BI and reporting tools such as Power BI, Tableau, or similar technologies. - Experience in advanced data management, data processing, and data science-related exploration to derive insights for business decision-making. - Working knowledge of modern infrastructure automation technology stacks and the ability to choose the best tool for each task. - Understanding of various Agile principles, methodologies, and frameworks, particularly those scaled for enterprise-level operations. - Willingness to facilitate knowledge transfer, coach others, and support their learning. - Strong analytical skills, quick grasp, and proactive approach to independent work. - Demonstrated ability to think creatively and analytically in problem-solving scenarios. - Excellent written and verbal communication skills, with the capability to explain new ideas and concepts to both technical and non-technical audiences. - Effective communication with customers, ensuring clarity and transparency. - Eagerness for self-directed learning, with a commitment to continuously enhance skills and knowledge. Please note that the job description does not include any additional details about the company.