Senior / Lead Platform Forward Deployed Engineer - Cogentiq I2C

About this role

Not quite right? These jobs in Bengaluru match the same skills — apply to a few to improve your chances.

Specialist, Application Development- Azure Infrastructure, backend python, API development

AT&T

RemoteBengaluru

Apply

Software Engineer II - Python, Fast API, Django, Microservices, SQL, Azure, GIT

Blue Yonder

In OfficeBengaluru

Apply

Senior Technology Automation Engineer(| Azure DevOps | Azure Cloud | Terraform | C#/Python | API)

Assurant

In OfficeBengaluru

Apply

Sr Software Engineer - C++ , Python, Shell scripting & Azure/Cloud

Blue Yonder

In OfficeBengaluru

Apply

Skills you'll use

What you'll do

• Own the deployment architecture of client installations from environment readiness through hypercare: bundle strategy, environment topology (Dev, QA, production; per-client catalogs), release sequencing, and sign-off that the installation meets the validation standard.
• Navigate Unity Catalog and platform governance Client and internal IT control catalog and metastore provisioning, storage decisions, and access models. You will assess what their governance model means for our setup scripts, negotiate provisioning paths, and know when a shared-infrastructure convenience creates an SOW, NDA, or data-isolation problem that must be escalated rather than worked around.
• Set and enforce the platform engineering standards: idempotent, rerunnable deployments; fail-fast error handling with no silent except-and-continue paths; environment-variable-driven parameterisation with a single point of change per client value; and configuration conventions that hold across Databricks today and Fabric tomorrow.
• Own the shared utilities architecture: interface-function contracts and factory-pattern abstractions across Databricks, Fabric, PostgreSQL, SQL Server, and storage back ends, packaged as versioned wheel files through Azure Artifactory, so swapping a client's platform is a configuration change, not a rewrite.
• Make the hard ingestion calls: auto-loader versus custom conflict-driven ingestion when the client will not provision Databricks, checkpoint and reprocessing strategy, retry and alerting design per pipeline, and writeback reliability to the application database.
• Run incident command during deployment and hypercare. When a deployment breaks in a client environment, you run the incident: triage across the data estate, the application database, and upstream ERP feeds; communicate honestly with the client; and land the fix and the post-incident correction to the playbook.
• Own the deployment playbook as a product. The quick-start guides, validation suites, and synthetic data configurations you leave behind must make the next deployment cheaper. The bar is that a newcomer deploys the platform from your playbook with one setup script.
• Coach junior Platform FDEs, reviewing their work against the standards you set and growing them toward deployment ownership.

About Fractal

Searching for “Fractal jobs” or “jobs at Fractal”? You’re in the right place.