Packaged/SaaS Application Engineer
Project Role Description : Configure and support packaged or SaaS applications to adapt features, manage releases, and ensure system stability. Use standard tools, APIs, and low-code platforms to align solutions with business needs while preserving compatibility and performance.
Must have skills : Site Reliability Engineering
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Packaged or Software as a Service Application Engineer, a typical day involves configuring and supporting packaged or SaaS applications to meet evolving business requirements. This role requires managing application features, overseeing release processes, and ensuring the overall stability and performance of systems. The engineer works with various tools, application programming interfaces, and low-code platforms to tailor solutions that align with organizational goals while maintaining compatibility across different environments. Collaboration with multiple teams and continuous monitoring of application health are integral parts of daily activities to deliver seamless user experiences.
Experience Required
5–7+ years of experience in Cloud Engineering, Site Reliability Engineering, DevOps, DataOps, or Platform Engineering
Minimum 3 years of hands-on experience with Terraform and AWS-based data platforms
Minimum 2 years of experience with at least two of the following: Databricks, Snowflake, dbt, Immuta, or Astronomer/Airflow
Role Summary
The Cloud & Data Site Reliability Engineer will design, automate, and operate secure, scalable, and highly reliable cloud-native data platforms across multi-account and multi-region AWS environments. The role combines Cloud Engineering, DataOps, DevOps, observability, automation, and SRE practices to support enterprise analytics, AI/ML, and data modernisation initiatives.
The engineer will be responsible for platform availability, infrastructure automation, incident management, performance optimisation, data governance, security, cost control, and integration across AWS, Databricks, Snowflake, dbt, Immuta, and Astronomer/Airflow.
Primary Skills
1. Terraform Enterprise
o Advanced Terraform module development and composition
o Workspace strategy, remote state, policy-as-code, and semantic versioning
o Dynamic blocks, loops, conditionals, collections, validations, and preconditions
o Multi-account and multi-region infrastructure deployment
o Terraform testing, documentation, migration, and cross-repository dependencies
2. AWS Cloud Engineering
o AWS S3, IAM, KMS, Lambda, Glue, Athena, CloudWatch, EventBridge, and Step Functions
o AWS Lake Formation and Glue Data Catalog
o Multi-account, multi-environment, and multi-region AWS architecture
o Private networking, cross-account access, disaster recovery, and high availability
o AWS security, governance, compliance, and cost optimisation
3. Data Platform Engineering
o Databricks administration, Unity Catalog, clusters, notebooks, jobs, and MLflow
o Snowflake administration, RBAC, storage integration, warehouse lifecycle, and performance tuning
o dbt models, macros, tests, documentation, and target configuration
o Astronomer/Airflow-based orchestration
o Apache Iceberg and Bronze/Silver/Gold data architecture
4. Python and Automation
o Python scripting for cloud automation, Lambda functions, validation, and platform workflows
o PySpark and Pandas
o API integration and configuration management
o Automation of operational activities and remediation workflows
5. GitLab CI/CD and DevOps
o GitLab CI/CD pipeline architecture
o Parallel and matrix-based deployments
o Automated testing, security scanning, artifact management, and production approval gates
o GitOps promotion, secrets management, and concurrency controls
o Multi-environment deployment across development, test, UAT, and production
6. Site Reliability Engineering and Observability
o SLIs, SLOs, SLAs, error budgets, and capacity planning
o Incident response, root-cause analysis, post-incident reviews, and operational runbooks
o Metrics, monitoring, dashboards, logging, tracing, and anomaly detection
o Self-healing, automated recovery, retries, checkpointing, and dead-letter handling
o Performance optimisation across storage, compute, networking, and data pipelines
Pune
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