Data Engineer-Enterprise Data Product

My responsibilities: - Maintain, develop, and optimize the global datalake environment, ensuring high data quality, reliability, and overall performance - Design and implement high-performance data processing pipelines and workflows utilizing Python, Spark, and Databricks - Manage scalable and efficient data integration and processing solutions using Azure Data Factory, Databricks, and Event Hub - Establish robust data management processes and execute advanced data querying and quality control with SQL and big data technologies - Automate operational tasks and support infrastructure maintenance by leveraging shell scripting and foundational UNIX knowledge - Support data modeling initiatives for coherent structure design and document all technical processes to ensure operational continuity The knowledge I own: - Strong background and understanding of database data management (general SQL knowledge, data querying, data quality control) - Strong programming knowledge in Python (pandas, numpy) - Advanced level Big Data / data lake framework (Spark, Databricks) - Strong cloud knowledge and handling of Azure Data Factory, Databricks, Event Hub - Basic familiarity with UNIX operating system, especially shell scripting - Basic understanding of network level problems and connectivity requirements - Basic Understanding data modelling principes - Data-centric mindset - Structured, analytical thinking - Strong communication skills - Well-organized - Can work in a multi-shift operation (Monday to Friday, 07:00 AM - 22:00 PM) + on-call (weeknights, weekends and public holidays) The offer that would convince me: - A constantly growing organization and increasing opportunities - Secure, long-term job opportunity - Varied and engaging job responsibilities - Outstanding salary - Flexible work arrangements - Home office possibility