Seeking a seasoned AWS Data Engineer to spearhead the design, development, and upkeep of robust data pipelines and data lake solutions on AWS. Candidates should possess proven expertise in AWS data services, SQL, Spark, ETL processes, and contemporary data lake architectures. Prior experience in the Banking and Financial Services (BFSI) sector is highly advantageous. This role involves close collaboration with business analysts, data architects, and reporting teams to construct reliable, high-performance data pipelines essential for enterprise analytics and regulatory compliance.

This is an exciting opportunity to contribute to significant data modernization and migration initiatives.

Key duties include architecting and implementing scalable ETL/ELT pipelines within the AWS ecosystem. You will build and manage enterprise-grade Data Lakes using Amazon S3 and Apache Iceberg. Developing and optimizing Spark applications with PySpark on Amazon EMR, alongside creating and refining SQL queries via Amazon Athena, will be crucial. The role also involves designing and maintaining dimensional data models, implementing incremental loading and CDC processes, and developing data ingestion frameworks from diverse sources. Performance optimization of Spark jobs for efficiency and cost-effectiveness, along with monitoring and troubleshooting data pipelines, are integral. You'll establish data quality checks, collaborate with stakeholders on analytics requirements, and participate in code reviews and testing cycles. Furthermore, creating technical documentation and adhering to data governance, security, and compliance standards are essential.

A minimum of 3 to 8 years of dedicated experience in Data Engineering is required. Essential skills include strong proficiency with AWS Data Services, hands-on PySpark development on EMR, and advanced SQL development with query optimization. Candidates must demonstrate experience working with large datasets, building Data Lakes and Data Marts, and ideally, experience with Apache Iceberg tables. Building production-grade ETL pipelines and a solid understanding of data reconciliation and validation techniques are also necessary. Familiarity with Agile/Scrum methodologies is expected. Experience in the Banking or Financial Services domain is preferred, as is knowledge of regulatory reporting and relevant certifications like AWS Certified Data Engineer – Associate.