Lead Data Science Engineer

As a Data Engineering Lead, you will have the responsibility to lead and mentor a high-performing data pod consisting of data engineers, data analysts, and BI developers. Your role will involve designing, implementing, and maintaining ETL pipelines and data workflows to support real-time and batch processing. Additionally, you will be tasked with architecting and optimizing data warehouses for scale, performance, and security. Your expertise in advanced data analysis and modeling will be crucial in extracting insights to support business decisions. You will also lead data science initiatives such as predictive modeling, NLP, and statistical analysis. Key Responsibilities: - Lead and mentor a high-performing data pod composed of data engineers, data analysts, and BI developers. - Design, implement, and maintain ETL pipelines and data workflows to support real-time and batch processing. - Architect and optimize data warehouses for scale, performance, and security. - Perform advanced data analysis and modeling to extract insights and support business decisions. - Lead data science initiatives including predictive modeling, NLP, and statistical analysis. - Manage and tune relational and non-relational databases (SQL, NoSQL) for availability and performance. - Develop Power BI dashboards and reports for stakeholders across departments. - Ensure data quality, integrity, and compliance with data governance and security standards. - Work with cross-functional teams (product, marketing, ops) to turn data into strategy. Qualifications Required: - PhD in Data Science, Computer Science, Engineering, Mathematics, or related field. - 7+ years of hands-on experience across data engineering, data science, analysis, and database administration. - Strong experience with ETL tools (e.g., Airflow, Talend, SSIS) and data warehouses (e.g., Snowflake, Redshift, BigQuery). - Proficient in SQL, Python, and Power BI. - Familiarity with modern cloud data platforms (AWS/GCP/Azure). - Strong understanding of data modeling, data governance, and MLOps practices. - Exceptional ability to translate business needs into scalable data solutions. Note: The job description does not contain any additional details about the company.,