DevOps Engineer / DevOps Consultant

Role Summary
We are seeking a hands-on DevOps Engineer / DevOps Consultant to support a cloud-based product that ingests data from multiple sources, performs ETL processing, stores data in Amazon RDS for PostgreSQL, and provides AI-enabled functionality using AWS services such as Amazon Bedrock and Amazon Bedrock AgentCore.
The successful candidate will be responsible for designing, implementing, automating, and operating secure and reliable AWS infrastructure, data-processing workflows, database deployments, CI/CD pipelines, and production observability. All infrastructure, configuration, database schema changes, and application-related deployments must be version-controlled and promoted through controlled CI/CD pipelines.
The role requires strong ownership, independent execution, production troubleshooting capability, and close collaboration with application, data, AI, security, and infrastructure teams.

Key Responsibilities
Cloud and Infrastructure Engineering
Design, deploy, and manage secure, scalable, highly available AWS infrastructure using Terraform.
Support AWS services including VPC, IAM, S3, Lambda, API Gateway, ECS, CloudFront, ACM, WAF, KMS, Secrets Manager, CloudWatch, and SNS.
Develop reusable and standardized Terraform modules aligned with security, governance, and operational standards.
Manage infrastructure configuration, environment promotion, and changes exclusively through source-controlled CI/CD pipelines.
Identify opportunities to improve reliability, performance, standardization, and AWS cost efficiency.

ETL and Workflow Orchestration
Support data ingestion and ETL workloads that process data from multiple internal and external sources.
Operate and deploy AWS Glue jobs, Crawlers, Data Catalog resources, connections, IAM roles, and runtime configurations.
Manage AWS Step Functions workflows used to orchestrate ingestion, transformation, validation, and downstream processing.
Implement monitoring for job status, execution duration, failures, data freshness, and processing outcomes.

Amazon RDS for PostgreSQL
Provision and manage Amazon RDS for PostgreSQL using Terraform and CI/CD automation.
Support database availability, backups, point-in-time recovery, encryption, parameter groups, maintenance, upgrades, and capacity management.
Support database backup validation, restore testing, failover procedures, and operational recovery.
Ensure database changes are deployed safely and consistently across environments.
Database DDL and Schema Management
Manage PostgreSQL DDL and schema changes through version-controlled and auditable CI/CD processes.
Automate deployment of tables, schemas, indexes, constraints, views, functions, procedures, roles, grants, and other approved database objects.
Ensure production DDL changes are not performed manually as part of the standard deployment process.

AWS AI and Agent-Based Services
Support infrastructure and deployment automation for Amazon Bedrock and Amazon Bedrock AgentCore capabilities.
Manage related IAM permissions, Lambda functions, APIs, knowledge bases, guardrails, configuration, and runtime dependencies.
Implement secure deployment patterns for AI-related infrastructure and configuration.
Monitor AI service availability, invocation failures, latency, throttling, quotas, and cost.
Collaborate with application and AI engineering teams to improve the reliability, security, and operational readiness of AI-enabled functionality.

Observability and Incident Response
Design and maintain observability for ETL pipelines, Step Functions, RDS PostgreSQL, APIs, Lambda functions, containers, and AWS AI services.
Create and manage Amazon CloudWatch metrics, logs, dashboards, Logs Insights queries, metric filters, and alarms.
Configure Amazon SNS for notification routing and integrate CloudWatch alarms with PagerDuty.

Develop actionable s for:
Glue job and Step Functions failures
Workflow timeouts and throttling
Data freshness and processing delays
RDS availability, performance, connection, and storage issues
API, Lambda, container, Bedrock, and AgentCore errors
CI/CD deployment failures
Tune thresholds and routing to reduce noise and ensure effective incident response.
Create operational runbooks and participate in incident management, root cause analysis, and post-incident remediation.
CI/CD and Automation
Design, build, and maintain GitLab CI/CD pipelines for infrastructure, application, ETL, database, and AI-related deployments.
Include automated stages for testing, Terraform validation, security scanning, DDL validation, policy checks, approvals, deployment, and post-deployment verification.
Promote changes through development, test, staging, and production environments using controlled release processes.
Ensure deployment artifacts are versioned, traceable, and consistently promoted.
Secure pipeline credentials and integrate with approved secrets-management solutions.
Security and Compliance
Apply security-by-design and least-privilege principles across AWS infrastructure, databases, ETL workloads, pipelines, and AI services.
Implement encryption in transit and at rest, secure secrets management, private networking, IAM controls, and appropriate resource policies.
Integrate vulnerability scanning, code analysis, and compliance checks into CI/CD workflows, including tools such as Checkmarx.
Ensure credentials and sensitive configuration are not stored in source code or pipeline definitions.
Maintain auditability for infrastructure, database, deployment, access, and operational changes.
Documentation and Collaboration
Maintain clear documentation covering architecture, infrastructure, CI/CD pipelines, database deployments, ETL operations, monitoring, incident response, and support procedures.
Work effectively with application, data engineering, AI, database, security, and infrastructure teams.
Independently manage assigned workstreams, resolve issues proactively, and communicate risks and dependencies clearly.

Required Qualifications
Strong hands-on AWS experience, particularly with AWS Glue, Step Functions, RDS PostgreSQL, CloudWatch, SNS, Lambda, S3, IAM, VPC, API Gateway, and related services.
Practical experience with Amazon Bedrock and/or Amazon Bedrock AgentCore, including deployment, IAM, monitoring, and operational support.
Strong Terraform experience, including reusable modules, remote state, environment management, validation, and CI/CD integration.
Strong experience designing and maintaining GitLab CI/CD pipelines.
Experience deploying PostgreSQL DDL and schema changes through automated, version-controlled pipelines.
Experience with CloudWatch alarms, SNS notification routing, and PagerDuty integration.
Strong understanding of ETL operations, workflow orchestration, retries, failure handling, and data-processing dependencies.
Hands-on Docker and container troubleshooting experience.
Strong Linux administration and troubleshooting skills.
Proficiency in shell scripting; Python experience is desirable.
Experience integrating security scanning and compliance controls into engineering workflows.
Strong understanding of AWS networking, IAM, encryption, secrets management, and operational security.

Candidate Profile
The ideal candidate will demonstrate:
A hands-on, automation-first approach to DevOps and platform engineering.
Strong experience supporting production data integration and ETL platforms.
Practical knowledge of RDS PostgreSQL operations and automated DDL deployment.
The ability to troubleshoot across AWS, databases, ETL workflows, CI/CD, Linux, networking, containers, and AI services.
Experience building reliable observability and incident-management processes using CloudWatch, SNS, and PagerDuty.
Familiarity with AWS Bedrock and AgentCore operational requirements.
The ability to work independently, take ownership, and deliver with minimal supervision.
Strong communication, documentation, and cross-functional collaboration skills.
A commitment to security, reliability, operational excellence, standardization, and cost optimization.

Core Principles
Hands-On Ownership: Take direct responsibility for implementation, troubleshooting, deployment, and operational outcomes.
Automation First: Manage infrastructure, database changes, ETL workflows, and application deployments through CI/CD.
Security by Design: Apply least privilege, encryption, secure networking, secrets management, and compliance controls from the outset.
Shift Left: Perform testing, validation, security scanning, and policy checks early in the delivery lifecycle.
Operational Excellence: Build reliable, observable, supportable, and well-documented platforms.
Data Integrity: Protect data throughout ingestion, transformation, storage, schema changes, and recovery processes.
Reusable Design: Promote modular Terraform, standardized pipelines, reusable deployment patterns, and DRY engineering practices.
Cost Optimization: Continuously improve AWS resource usage and operational efficiency without compromising reliability or security.