Design, build, and maintain the underlying infrastructure for a modern cloud-based data platform.
Implement and manage CI/CD processes for data pipelines and platform deployments across development and production environments.
Design and manage secure, scalable AWS-based data infrastructure, including IAM roles, permissions, policies, networking, and environment isolation.
Build and maintain orchestration, monitoring, alerting, and observability capabilities for data pipelines and platform services.
Support deployment, reliability, and operational excellence of data workloads running on technologies such as Spark, DBT, Airflow, Athena, and AWS services.
Collaborate closely with Data Engineers, Analysts, BI teams, and IT/Cyber teams to ensure secure and scalable data operations.
Monitor, troubleshoot, and optimize platform performance, availability, and cost efficiency.
Establish best practices for infrastructure-as-code, deployment standards, security, and production readiness.
Requirements
5+ years of hands-on experience in Data Engineering, Platform Engineering, DevOps, or Cloud Infrastructure roles.
Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Strong hands-on experience with AWS, including services such as IAM, S3, Athena, CloudWatch, networking, permissions, and security policies.
Experience managing development and production environments, deployment processes, and CI/CD pipelines.
Experience supporting and operating data platforms and pipelines in production environments.
Strong understanding of data engineering concepts and modern data architectures (batch and real-time).
Experience working with Spark, Airflow, and cloud-based data processing frameworks.
Strong Python and SQL skills.
Experience with monitoring, logging, alerting, and operational troubleshooting of data systems.
Experience with Infrastructure as Code tools (Terraform / CloudFormation) – Advantage
Experience with Kubernetes, containerized environments – Advantage
Experience with Kafka, Iceberg, Databricks, Snowflake – Advantage
Strong ownership and execution mindset, with the ability to work in fast-paced and ambiguous environments.