BENGALURU · FULLTIME
Senior Migration Engineer | CTC Upto 70 LPA
Round1 Jobs
Bengaluru · onsite · Posted 7d ago
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Section · 01
About this role
Company Description
Gallop is building an agentic migration platform to help organizations move Databricks environments from Azure and AWS to Google Cloud. The team combines hands-on engineering with automation to deliver repeatable migrations across data, infrastructure, governance, and supporting cloud services, with an emphasis on validation, security, and reliable production cutovers.
Role Description
The Senior Migration Engineer — Databricks to Google Cloud will execute end-to-end migrations, working directly with the product lead on scope, sequencing, and priorities. Responsibilities include assessing source environments, mapping dependencies, provisioning Google Cloud infrastructure, and migrating Databricks assets across identity, Unity Catalog, data, compute, jobs, pipelines, machine learning, and downstream consumption.
The engineer will also refactor supporting Azure and AWS services into Google Cloud equivalents, validate migrated workloads through parallel runs and reconciliation, and execute cutover, rollback, and source decommissioning. The role involves developing reusable automation, validating platform-generated code and Terraform, maintaining representative test environments, and documenting migration procedures, results, and risks.
Qualifications
- Hands-on engineering experience delivering at least one production Databricks migration across clouds, including cutover and rollback. Azure or AWS to Google Cloud experience is preferred.
- Typically 8+ years of data engineering experience, including 5+ years working hands-on with Databricks at enterprise scale.
- Strong Unity Catalog expertise, including metastores, storage credentials, external locations, grants, governed tags, row filters, column masks, and system tables.
- Practical experience with Databricks on Google Cloud and GCP networking, IAM, service accounts, Workload Identity Federation, Cloud Storage, and Storage Transfer Service.
- Proficiency in Python, SQL, PySpark, and the Databricks SDK, CLI, and REST APIs for discovery, migration, and automation.
- Delivered experience with modular Terraform using Google and Databricks providers, Databricks Asset Bundles, and CI/CD workflows.
- Production migration experience from either Azure or AWS, with working knowledge of the other and experience refactoring supporting cloud services.
- Ability to troubleshoot identity, networking, storage, streaming, orchestration, model serving, and performance issues across cloud environments.
- Strong validation and documentation practices, including reconciliation, dependency mapping, runbooks, logs, and rollback procedures.
- Working knowledge of GCP-native replatforming options such as Dataproc Serverless, Iceberg on Cloud Storage, BigLake, Dataplex, and Vertex AI.
- Ability to execute against defined milestones, collaborate with a product lead, and communicate risks and blockers early.
- Hands-on replatforming, AI-generated code validation, Hive Metastore-to-Unity Catalog upgrades, or delivery in regulated environments would be advantageous.
- Databricks Data Engineer Professional or Google Cloud Professional Data Engineer or Cloud Architect certifications are a plus.
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Section · 02