Data Engineer (Big Data)

As an experienced Data Engineering Architect with expertise in modern data engineering ecosystems, cloud-native data platforms, and large-scale streaming architectures, you will play a crucial role in designing scalable data pipelines, driving enterprise data transformation initiatives, and managing high-performing engineering teams. Key Responsibilities: - Design, develop, and maintain scalable enterprise data solutions for: - Data Generation - Data Collection - Data Processing - Data Transformation - Data Migration - Architect and implement modern cloud-native data platforms and streaming data pipelines. - Lead end-to-end ETL/ELT process design and implementation across enterprise systems. - Design robust and scalable real-time data processing solutions using Apache Kafka, Apache Flink, and DBT (Data Build Tool). - Drive architecture decisions for cloud-based data engineering and analytics platforms. - Ensure data quality, governance, reliability, and scalability across data ecosystems. - Collaborate with multiple engineering and business teams to drive strategic technical decisions. - Provide architecture-level solutions for enterprise-wide data engineering challenges. - Lead and mentor engineering teams while driving technical excellence and delivery standards. - Conduct knowledge-sharing sessions and technical training programs for teams. - Develop and maintain architecture documentation, workflow diagrams, and engineering standards. - Drive best practices around data modeling, streaming architectures, data governance, performance optimization, and data observability. Required Skills & Qualifications: - 12+ years of experience in data engineering, big data technologies, data platform architecture, and enterprise data solutions. - Strong expertise in DBT (Data Build Tool), Apache Kafka, Apache Flink, and Cloud Data Engineering. - Proven experience designing and implementing large-scale data pipelines, real-time streaming architectures, ETL/ELT frameworks, and enterprise data integration solutions. - Strong understanding of data quality frameworks, data governance, distributed data systems, and event-driven architectures. - Experience with cloud-based data platforms and architectures. - Strong stakeholder management and team leadership experience. - Excellent analytical, architectural, and problem-solving skills. Preferred Skills: - Exposure to Snowflake, Databricks, Airflow, Spark, and Lakehouse Architectures. - Experience with multi-cloud data ecosystems. - Familiarity with CI/CD and DevOps practices for data platforms. - Exposure to data observability and monitoring tools. In this role, you will need to demonstrate a strong architecture and systems-thinking mindset, lead enterprise-scale data transformation initiatives, exhibit mentoring and technical leadership capabilities, work effectively across cross-functional global teams, and be passionate about building scalable and reliable modern data platforms. As an experienced Data Engineering Architect with expertise in modern data engineering ecosystems, cloud-native data platforms, and large-scale streaming architectures, you will play a crucial role in designing scalable data pipelines, driving enterprise data transformation initiatives, and managing high-performing engineering teams. Key Responsibilities: - Design, develop, and maintain scalable enterprise data solutions for: - Data Generation - Data Collection - Data Processing - Data Transformation - Data Migration - Architect and implement modern cloud-native data platforms and streaming data pipelines. - Lead end-to-end ETL/ELT process design and implementation across enterprise systems. - Design robust and scalable real-time data processing solutions using Apache Kafka, Apache Flink, and DBT (Data Build Tool). - Drive architecture decisions for cloud-based data engineering and analytics platforms. - Ensure data quality, governance, reliability, and scalability across data ecosystems. - Collaborate with multiple engineering and business teams to drive strategic technical decisions. - Provide architecture-level solutions for enterprise-wide data engineering challenges. - Lead and mentor engineering teams while driving technical excellence and delivery standards. - Conduct knowledge-sharing sessions and technical training programs for teams. - Develop and maintain architecture documentation, workflow diagrams, and engineering standards. - Drive best practices around data modeling, streaming architectures, data governance, performance optimization, and data observability. Required Skills & Qualifications: - 12+ years of experience in data engineering, big data technologies, data platform architecture, and enterprise data solutions. - Strong expertise in DBT (Data Build Tool), Apache Kafka, Apache Flink, and Cloud Data Engineering. - Proven experience designing and implementing large-scale data pipelines, real-time streaming architectures, ETL/