AWS Infrastructure Engineer SME; Architect
Listed on 2026-03-01
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IT/Tech
Cloud Computing, Data Engineer, AWS, Systems Engineer
Overview
Apexon is a digital-first technology services firm specializing in accelerating business transformation and delivering human-centric digital experiences. We have been meeting customers wherever they are in the digital lifecycle and helping them outperform their competition through speed and innovation. Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, Dev Ops, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the unlimited opportunities digital offers.
Our reputation is built on a comprehensive suite of engineering services, a dedication to solving clients’ toughest technology problems, and a commitment to continuous improvement. Backed by Goldman Sachs Asset Management and Everstone Capital, Apexon now has a global presence of 15 offices (and 10 delivery centers) across four continents.
We are seeking a highly skilled AWS Infrastructure Engineer to design, build, and manage scalable, secure, and highly available AWS infrastructure. This role will be responsible for creating AWS infrastructure from the ground up, defining policies, roles and standards, and deploying and managing resources using Infrastructure as Code (Terraform). The engineer will also support data platforms, including S3, EMR, Kafka and other AWS services, ensuring performance, reliability, versioning, scalability and cost efficiency.
Key Responsibilities- Design and implement AWS cloud infrastructure following best practices for security, scalability, and availability
- Architect solutions across multiple availability zones for high availability and fault tolerance
- Define and enforce AWS resource naming standards and tagging strategies
- Implement IAM policies, bucket policies, and security controls aligned with organizational governance
- Manage core AWS services including VPC, EC2, S3, IAM, Cloud Watch, and EMR
- Design and manage Amazon S3 buckets, including:
- Bucket policies and access controls
- Encryption, versioning, and logging
- Define and implement S3 lifecycle management policies for cost optimization and data retention
- Establish data partitioning and versioning strategies for large-scale datasets
- Develop, deploy, and maintain AWS infrastructure using Terraform
- Create reusable Terraform modules and enforce IaC best practices
- Integrate Terraform deployments with CI/CD pipelines
- Perform infrastructure upgrades and changes with minimal downtime
- Design, deploy, and manage AWS EMR clusters
- Cluster sizing, node roles (master/core/task), and configurations
- Auto-scaling and performance tuning
- Manage cluster lifecycle (provisioning, scaling, patching, termination)
- Optimize Spark, Hive, and Hadoop workloads for performance and cost
- Integrate and manage Kafka for streaming data pipelines
- Define Kafka partitioning and scaling strategies
- Implement monitoring, logging, and alerting using Amazon Cloud Watch and related tools
- Troubleshoot infrastructure, EMR, and data platform issues
- Document architecture, standards, and operational procedures in Confluence
- Collaborate with data engineers, security teams, and application teams
- 10+ years of experience in AWS infrastructure and cloud engineering
- Strong hands-on experience with Terraform and Infrastructure as Code
- Deep knowledge of AWS services: S3, EC2, VPC, IAM, EMR, Cloud Watch
- Solid understanding of security best practices and policy management
- Hands-on experience with Big Data platforms (EMR, Spark, Hive, Hadoop)
- Experience with Kafka, including partitioning and scaling strategies
- Experience working in Linux-based environments
- AWS Certified Solutions Architect (Associate or Professional)
- AWS Certified Data Analytics – Specialty
- Familiarity with CI/CD tools (Git Hub Actions, Jenkins, Git Lab CI)
- Experience in large-scale or regulated enterprise environments
- AWS infrastructure is fully codified, repeatable, and secure
- EMR and Kafka platforms scale reliably with…
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