Packaged/SaaS Application Engineer

Overview

Configure and support packaged or SaaS applications to adapt features, manage releases, and ensure system stability, using standard tools, APIs, and low-code platforms.

What you'll do

• Configure and support packaged or SaaS applications to meet evolving business requirements.
• Manage application features and oversee release processes.
• Ensure overall stability and performance of systems.
• Use tools, application programming interfaces, and low-code platforms to align solutions with organizational goals while maintaining compatibility across environments.
• Collaborate with multiple teams and continuously monitor application health.
• Design, automate, and operate secure, scalable, and highly reliable cloud-native data platforms across multi-account and multi-region AWS environments.
• Support enterprise analytics, AI/ML, and data modernisation initiatives.
• Manage platform availability, infrastructure automation, incident management, performance optimisation, data governance, security, cost control, and integration across AWS, Databricks, Snowflake, dbt, Immuta, and Astronomer/Airflow.

What you'll need

• 15 years of full time education.
• Minimum 7.5 years of experience (must-have skill: Site Reliability Engineering).
• 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.
• Advanced Terraform module development and composition; workspace strategy, remote state, policy-as-code, and semantic versioning; dynamic blocks, loops, conditionals, collections, validations, and preconditions; multi-account and multi-region infrastructure deployment; Terraform testing, documentation, migration, and cross-repository dependencies.
• AWS S3, IAM, KMS, Lambda, Glue, Athena, CloudWatch, EventBridge, and Step Functions; AWS Lake Formation and Glue Data Catalog; multi-account, multi-environment, and multi-region architecture; private networking, cross-account access, disaster recovery, and high availability; AWS security, governance, compliance, and cost optimisation.
• Databricks administration, Unity Catalog, clusters, notebooks, jobs, and MLflow; Snowflake administration, RBAC, storage integration, warehouse lifecycle, and performance tuning; dbt models, macros, tests, documentation, and target configuration; Astronomer/Airflow-based orchestration; Apache Iceberg and Bronze/Silver/Gold data architecture.
• Python scripting for cloud automation, Lambda functions, validation, and platform workflows; PySpark and Pandas; API integration and configuration management; automation of operational activities and remediation workflows.
• GitLab CI/CD pipeline architecture; parallel and matrix-based deployments; automated testing, security scanning, artifact management, and production approval gates; GitOps promotion, secrets management, and concurrency controls; multi-environment deployment across development, test, UAT, and production.
• SLIs, SLOs, SLAs, error budgets, and capacity planning; incident response, root-cause analysis, post-incident reviews, and operational runbooks; metrics, monitoring, dashboards, logging, tracing, and anomaly detection; self-healing, automated recovery, retries, checkpointing, and dead-letter handling; performance optimisation across storage, compute, networking, and data pipelines.

Details

• Location: Pune.