DevOps Engineer

Join our Infrastructure & Platform Engineering team to automate cloud infrastructure, CI/CD pipelines, and containerized services across AWS, GCP, and private cloud environments. You will drive automation, enhance platform reliability and security, and gain hands-on experience with our next-generation AWS Lakehouse ecosystem, including Databricks, Airbyte, Apache Iceberg, Polaris, and Cube

Job Responsibilities

Assist in provisioning, configuring, and managing multi-cloud infrastructure across AWS, GCP, and Private Cloud / on-premises environments using Terraform.Maintain modular, reusable, version-controlled IaC codebases adhering to enterprise security baselines and least-privilege principles.Support virtual networks, VPC peering, cloud interconnects, IAM role boundaries, and hybrid connectivity.Build, optimize, and maintain automated CI/CD build and delivery pipelines using Bitbucket Pipelines and self-hosted Bitbucket Runners.Package application workloads and platform services into standardized, secure, and lightweight container images (Docker).Manage Kubernetes cluster deployments and workload configurations using ArgoCD following GitOps paradigms.Facilitate seamless environment promotion (Dev, Staging, Production), configuration drift detection and automated rollback workflows.Support deployment, orchestration, and infrastructure automation for our AWS-based Modern Data Lakehouse platform.Assist in configuring and operating Apache Iceberg table storage formats and metadata layers on AWS S3.Maintain and govern metadata registries with Apache Polaris catalog for cross-engine Iceberg interoperability.Support Databricks workspace lifecycle, cluster provisioning policies and Unity/cloud IAM integrations.Manage Airbyte deployment infrastructure (scaling worker pools, orchestrating connectors and scheduling ELT ingestion).Operate Cube semantic layer instances, pre-aggregation caching stores and BI connection interfaces.Assist in monitoring platform health, cluster capacity and data pipeline throughput using observability and monitoring tools (TrueWatch, Prometheus, Grafana, Datadog, AWS CloudWatch).Support incident troubleshooting, root cause analysis (RCA) and service reliability improvements.Implement security controls including container vulnerability scanning, secrets management (AWS Secrets Manager / Vault), and security audits.Support annual VAPT, PCI DSS, IA assessments and external audits.Work with stakeholders to ensure platform reliability, security and operational excellence.Use Generative AI and automation to redesign workflows, reduce repetitive work and human error, improve decision quality, and build the team's strategic consulting capabilityAny ad hoc duties as assigned

Job Requirements

Bachelor’s degree in computer science, Software Engineering, Information Technology, STEM disciplines, or equivalent practical experience and relevant technical certificationsCandidate with strong DevSecOps, Cloud Engineering, Systems Operations or IT Infrastructure is preferredSolid understanding of Linux/Unix operating systems, shell scripting (Bash) and core networking principles (TCP/IP, DNS, VPNs, Subnets, routing).Assist in monitoring platform health, cluster capacity and data pipeline throughput using observability and monitoring tools (TrueWatch, Prometheus, Grafana, Datadog, AWS CloudWatch).Familiar with setting up, maintaining or auto-scaling self-hosted Bitbucket Runners in private cloud or VPC setups.Practical coursework or hands-on experience with at least one major public cloud platform (AWS preferred, or GCP), with exposure to high availability architectures, disaster recovery planning and cost optimization best practices.Strong working knowledge of AWS S3 object storage optimization, partitioning schemes and lifecycle rules.Familiar with Terraform for infrastructure as code (IaC), including declarative cloud resource provisioning and infrastructure managementSolid understanding of Docker containerization, Kubernetes fundamentals and GitOps principles.Familiar with tools such as ArgoCD, Bitbucket Pipelines, GitHub Actions, or GitLab CI/CD for automated application delivery and deploymentHands-on experience or familiarity with Kubernetes (EKS, GKE, or AKS), including workload deployment, Helm chart management, service mesh implementation (Istio/Linkerd and container security and operational best practices will be plusProficient in Python, Go, Ruby, Bash for building custom tooling and automating complex operational workflowsHands-on exposure to or genuine curiosity in Lakehouse technologies: Databricks, Apache Iceberg, Polaris Catalog, Airbyte, or Cube is preferredAWS Certified Solutions Architect / SysOps Administrator, HashiCorp Certified: Terraform Associate or Databricks Certified Associate will be an advantage