Description

Key Skills: Apache Spark, AWS Glue, Apache Iceberg, Apache Kafka, Apache Flink, AWS S3, Python, Scala, SQL, Data Lake Architecture

Good to Have Skills: AWS Lambda, EKS (Elastic Kubernetes Service), Step Functions, Infrastructure as Code (IaC), DataOps, data observability, data governance, agentic frameworks, AI-driven workflows, Docker, Kubernetes, AWS certifications, experience in financial services or regulated industries, Master's degree in related technical field.

Roles & Responsibilities:

• Design and architect end-to-end data solutions from ingestion through transformation, storage, and analytics that are scalable, reliable, and high-performing at enterprise scale.
• Define and enforce data architecture standards and best practices for both batch and real-time processing pipelines.
• Build and optimize scalable data ingestion, transformation, and analytics solutions using enterprise-grade technologies.
• Develop and manage batch and streaming pipelines for real-time data processing across the organization.
• Implement Data Lake architectures including data organization, partitioning strategies, governance, and efficient access patterns.
• Design and deploy cloud-native data solutions using various AWS services for optimal performance and cost efficiency.
• Implement Infrastructure as Code practices for reproducible, secure, and scalable deployments across environments.
• Identify opportunities to eliminate or automate remediation of recurring issues and improve operational stability through monitoring frameworks.
• Build automated, self-healing data operations using agentic frameworks and AI-driven workflows for intelligent monitoring and optimization.
• Provide technical leadership and mentorship to data engineering team members, fostering strong engineering practices and operational excellence.
• Collaborate with cross-functional partners to translate business requirements into robust technical solutions and establish data quality standards.

Experience Required: 5+ years of applied experience in software engineering with formal training or certification on software engineering concepts. Demonstrated ability to architect and deliver large-scale enterprise data platforms from ingestion to analytics.

Education: Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field

Key Skills

Education

Any Graduate