Lead AWS Data Engineer

As a Data Engineer, your role involves building products in the data analytics space with a focus on shipping high-quality data products and contributing to the overall company and product development. You should possess the right attitude, aptitude, skills, empathy, compassion, and a hunger for learning. Here are the key responsibilities and qualifications required for this position: **Key Responsibilities:** - Understand business requirements and implement scalable solutions. - Translate complex technical and functional requirements into detailed designs. - Develop a highly scalable, reliable, and high-performance data processing pipeline for extracting, transforming, and loading data from various systems to the Enterprise Data warehouse/Data Lake/Data Mesh. - Provide research, high-level design, and estimates for data transformation and data integration from source applications to end-use. - Explore alternatives for data storing and processing to ensure streamlined solutions. - Create end-to-end data products and operationalize them in cloud/in-house servers. **Qualifications Required:** - Minimum 6-10 years of progressive experience in building solutions in Big Data environments. - Strong ability to build robust and resilient data pipelines that are scalable, fault-tolerant, and reliable in terms of data movement. - Hands-on experience with Apache Spark using Python for batch and stream processing. - Knowledge and experience in batch and stream data processing. - Exposure to working on projects across multiple domains. - At least 6 months of hands-on experience with Apache Kafka. - Proficiency in SQL and NoSQL technologies. - Minimum 3+ years of experience with AWS services such as S3, DMS, Redshift, Glue, Lambda, Kinesis, MSK, or similar services from Azure/GCP. - Strong analytical and quantitative skills, comfortable handling large datasets. - Excellent written and verbal communication skills.,