Job Summary
Experience
- 17–23 years of overall experience in Data Engineering, Analytics, or Cloud Platforms.
- 10+ years of customer-facing leadership experience in enterprise environments.
- Proven experience in handling teams of 100+ people.
- Experience working in global delivery models, including offshore teams.
Technical Leadership & Architecture
- Provide end-to-end technical leadership for enterprise-scale data platforms across GCP and Azure Data ecosystems.
- Architect and govern modern data platforms including Lakehouse, Data Mesh, Data Fabric, and advanced analytics architectures.
- Lead solution design using technologies such as:
- Google Cloud: BigQuery, Dataflow, Dataproc, Cloud Composer, Pub/Sub, Vertex AI
- Microsoft Azure: Azure Data Factory, Azure Synapse, Azure Databricks, Azure Data Lake, Fabric, Power BI
- Drive adoption of best practices in Data Engineering, DataOps, MLOps, security, and governance.
- Review and approve architecture designs, ensuring scalability, performance, cost optimization, and compliance.
People & Organization Leadership
- Build, lead, and scale large teams of 100+ data engineers, architects, and leads across onshore/offshore models.
- Establish strong execution culture with focus on quality, velocity, and innovation.
- Mentor senior technical leaders and create succession pipelines.
Communication & Leadership (Must Have)
- Excellent communication and executive presentation skills.
- Ability to articulate complex technical concepts to non-technical stakeholders.
- Strong written and verbal communication for proposals, presentations, and strategy documents.
Key Responsibilities
Communication & Leadership (Must Have)
- Excellent communication and executive presentation skills.
- Ability to articulate complex technical concepts to non-technical stakeholders.
- Strong written and verbal communication for proposals, presentations, and strategy documents.
Skill Requirements
- Provide end-to-end technical leadership for enterprise-scale data platforms across GCP and Azure Data ecosystems.
- Architect and govern modern data platforms including Lakehouse, Data Mesh, Data Fabric, and advanced analytics architectures.
- Lead solution design using technologies such as:
- Google Cloud: BigQuery, Dataflow, Dataproc, Cloud Composer, Pub/Sub, Vertex AI
- Microsoft Azure: Azure Data Factory, Azure Synapse, Azure Databricks, Azure Data Lake, Fabric, Power BI
- Drive adoption of best practices in Data Engineering, DataOps, MLOps, security, and governance.
- Review and approve architecture designs, ensuring scalability, performance, cost optimization, and compliance.