Lead Data Engineer

As a Data Engineer IV at Flipkart, you will play a critical role in shaping the company's data ecosystem at scale. You will partner closely with business and analytics teams to design and build robust, scalable, and high-performance data platforms and pipelines that power decision-making across the organization. Key Responsibilities: - Collaborate closely with Analysts, Product Managers, and Business stakeholders to understand complex business problems across Flipkart's ecosystem. - Translate business requirements into scalable and efficient data solutions. - Drive data architecture decisions aligned with business goals. - Design and build highly scalable, reliable, and efficient data pipelines. - Develop and maintain Common Data Models (CDMs) that standardize data across domains. - Ensure pipelines are optimized for large-scale data processing and diverse business use cases. - Architect data solutions by balancing: Performance, Scalability, Cost efficiency, Data modeling principles, Flexibility for evolving business needs. - Lead design reviews and influence best practices in data engineering. - Work extensively with modern big data technologies, including Apache Spark, Apache Flink, Apache Kafka, Google BigQuery, Dataproc, and Apache Iceberg. - Evaluate and adopt new technologies to improve platform capabilities. - Build systemic frameworks to monitor, measure, and improve data quality. - Implement automated checks, anomaly detection, and data validation systems. - Drive root cause analysis and resolution of data issues across pipelines. Qualifications Required: - Bachelor's/Master's degree in Computer Science, Engineering, or a related field. - 8-12+ years of experience in data engineering or related fields. - Strong experience in building large-scale distributed data systems. Preferred Qualifications: - Deep expertise in distributed computing frameworks like Spark/Flink. - Strong understanding of data modeling techniques (OLAP, dimensional modeling, etc. ). - Experience with real-time and batch data processing architectures. - Proven ability to design systems handling high data volume and velocity. - Strong problem-solving skills and ability to work in ambiguous environments. Note: Omitting any additional details of the company as it is not provided in the Job Description. As a Data Engineer IV at Flipkart, you will play a critical role in shaping the company's data ecosystem at scale. You will partner closely with business and analytics teams to design and build robust, scalable, and high-performance data platforms and pipelines that power decision-making across the organization. Key Responsibilities: - Collaborate closely with Analysts, Product Managers, and Business stakeholders to understand complex business problems across Flipkart's ecosystem. - Translate business requirements into scalable and efficient data solutions. - Drive data architecture decisions aligned with business goals. - Design and build highly scalable, reliable, and efficient data pipelines. - Develop and maintain Common Data Models (CDMs) that standardize data across domains. - Ensure pipelines are optimized for large-scale data processing and diverse business use cases. - Architect data solutions by balancing: Performance, Scalability, Cost efficiency, Data modeling principles, Flexibility for evolving business needs. - Lead design reviews and influence best practices in data engineering. - Work extensively with modern big data technologies, including Apache Spark, Apache Flink, Apache Kafka, Google BigQuery, Dataproc, and Apache Iceberg. - Evaluate and adopt new technologies to improve platform capabilities. - Build systemic frameworks to monitor, measure, and improve data quality. - Implement automated checks, anomaly detection, and data validation systems. - Drive root cause analysis and resolution of data issues across pipelines. Qualifications Required: - Bachelor's/Master's degree in Computer Science, Engineering, or a related field. - 8-12+ years of experience in data engineering or related fields. - Strong experience in building large-scale distributed data systems. Preferred Qualifications: - Deep expertise in distributed computing frameworks like Spark/Flink. - Strong understanding of data modeling techniques (OLAP, dimensional modeling, etc. ). - Experience with real-time and batch data processing architectures. - Proven ability to design systems handling high data volume and velocity. - Strong problem-solving skills and ability to work in ambiguous environments. Note: Omitting any additional details of the company as it is not provided in the Job Description.