Architect Lead - Data engineering

Job Description We are looking for an experienced Architect Lead – Data Engineering to lead the design and implementation of enterprise-scale data platforms, data pipelines and cloud-based data solutions. Key Responsibilities: • Lead the architecture and design of scalable data engineering and data platform solutions. • Design and develop high-volume data pipelines using Apache Spark and PySpark . • Implement data warehousing and analytics solutions using Snowflake . • Design workflow orchestration using Apache Airflow . • Develop modern data lake/lakehouse solutions using Apache Iceberg . • Design real-time and event-driven data pipelines using Apache Kafka . • Develop ETL/ELT solutions using DBT and enterprise ETL frameworks . • Work with GBI ETL Framework and ensure integration across enterprise data platforms. • Leverage cloud computing technologies to build secure, scalable and highly available data solutions. • Provide technical leadership, architecture guidance and mentoring to data engineering teams. • Drive performance tuning, data quality, scalability and reliability of data platforms. • Collaborate with business and technology stakeholders to translate requirements into technical solutions. • Explore and implement appropriate Artificial Intelligence capabilities within data platforms. Requirements: • Minimum 10 years of experience in data engineering, big data or data architecture. • Strong hands-on experience with Spark, PySpark, Snowflake, Airflow, Kafka and Iceberg . • Strong experience in ETL/ELT frameworks and DBT . • Experience with cloud-based data platforms and modern data architecture. • Experience designing large-scale data pipelines and lakehouse architectures. • Exposure to Artificial Intelligence / AI-based data solutions. • Strong analytical, problem-solving, communication and technical leadership skills. • Degree in Computer Science, Information Technology, Engineering or a related discipline.