a global pioneer of RADAR systems for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance. Were seeking a data Tech Lead to drive technical excellence in data engineering and analytics. As the go-to expert, you'll set the technical direction, optimize data pipelines, and tackle programming challengesclosing knowledge gaps, solving data -related questions, and streamlining operations. You'll also design scalable architectures, manage ETL workflows, and enhance data processing efficiency. Key Responsibilities: Oversee the technical aspects of data projects by making architectural and design decisions. Streamline existing operations and implement improvements with the teams collaboration. Guiding team members in technical matters, and supervising system modifications. Conducting Code reviews for data analysts, BI Analysts and data engineers. Bridge technical knowledge gaps within the data team, answering critical product-related questions.
Requirements:
5+ years of experience in data engineering & Big Data Analytics data Engineering & Automation Building robust, production-ready data pipelines using SQL Python, and PySpark, while managing ETL workflows and orchestrating data processes with Airflow (unmanaged) and Databricks Big Data Analysis & Distributed Processing: Expertise in Databricks (Spark, etc.) for handling large-scale data analytics with optimized efficiency. Cloud Infrastructure: Proficient in Cloud Services (preferably Azure) for data Storage and processing. data Architecture: Expertise in data architecture to ensure best practices in scaling, cost efficiency, and performance optimization. If you're passionate about building scalable data solutions and thrive in a fast-paced environment, wed love to hear from you!
5+ years of experience in data engineering & Big Data Analytics data Engineering & Automation Building robust, production-ready data pipelines using SQL Python, and PySpark, while managing ETL workflows and orchestrating data processes with Airflow (unmanaged) and Databricks Big Data Analysis & Distributed Processing: Expertise in Databricks (Spark, etc.) for handling large-scale data analytics with optimized efficiency. Cloud Infrastructure: Proficient in Cloud Services (preferably Azure) for data Storage and processing. data Architecture: Expertise in data architecture to ensure best practices in scaling, cost efficiency, and performance optimization. If you're passionate about building scalable data solutions and thrive in a fast-paced environment, wed love to hear from you!
This position is open to all candidates.
