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Tier-1 brand, metro location, popular data-engineer title, and broad skillset create high applicant competition.
Core data engineering skills transfer across industries, but Cloudera/CDP and payments context add moderate specificity.
Mandatory technical stack (Scala/Python/Java, CDP/Spark, Cloudera Manager, AWS) and Lead seniority drive strict shortlisting.
Design, develop and maintain backend data services and pipelines using Scala, Python, Java on Cloudera Data Platform and Spark for batch and streaming workloads.
Build and integrate AI-powered agents for anomaly detection, workflow automation, and intelligent automation to improve system scalability and reduce manual effort.
Develop and support cloud-based data and compute workloads in AWS and Databricks, enabling reliable backend data interfaces for analytics and business teams.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
Proven hands-on experience with Scala, Python, and/or Java in backend or data intensive systems.
Experience working with Cloudera Data Platform (CDP), Spark, and Cloudera Manager for cluster monitoring and administration.
Work Experience Required: Not explicitly mentioned in the JD.
Strong backend and distributed data platform engineering expertise focused on large scale data processing including batch and streaming workloads.
Experience designing and implementing AI-driven agents or intelligent automation at scale to support operational workflows.
Familiarity with cloud platforms (AWS), Databricks, and hybrid cloud architectures to support scalable data engineering solutions in a complex enterprise environment.