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Salary
≈ $30k – $66k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp

First seen by Alion on Aug 20, 2026.

Overview
Company
Impact
Profile match
Sonata Software is an Indian IT services and technology company headquartered in Bengaluru that provides modernization engineering across cloud, data, AI, Microsoft Dynamics, test automation and managed services. Founded in 1986 and listed in India, it runs the Harmoni.AI enterprise platform and works with Fortune 500 clients in banking, retail, healthcare, manufacturing and technology, with a presence in the US, UK, Malaysia, Mexico, Australia, the DACH region and the Nordics. It hires data and cloud architects, MLOps and DevOps engineers, .NET and full-stack developers, identity and security specialists, SharePoint administrators and JD Edwards consultants.

Location : Bangalore, India (White Field, 5 days working from office).

Experience : 8+ Years.

About the Role :

We are seeking an experienced Lead Data Platform Architect to lead the organization's Data Hub strategy, architecture, and delivery.

This role will be responsible for driving regional and global data initiatives, partnering with business stakeholders to deliver scalable data solutions, and ensuring data accuracy, governance, security, and operational excellence across the enterprise data landscape.

The ideal candidate will possess strong expertise in Databricks, Azure, Data Engineering, and Modern Lakehouse Architectures, combined with proven leadership experience in managing teams and delivering enterprise-scale data transformation programs.

Key Responsibilities :

- Lead and mentor a team of developers, providing technical guidance, task prioritization, and support for successful project delivery.

- Collaborate with global business stakeholders to understand data requirements and recommend best-in-class data solutions.

- Own the end-to-end delivery of Data Hub initiatives, ensuring quality, scalability, and timely execution.

- Manage project backlogs, create development tickets, prioritize work items, and track delivery progress.

- Design and implement modern Lakehouse architectures and enterprise data platforms using Databricks and Azure.

- Drive data governance, data quality, security, compliance, and metadata management across the Data Hub ecosystem.

- Establish and promote DataOps, CI/CD, automation, and engineering best practices.

- Enable Business Intelligence, Advanced Analytics, Machine Learning, and Generative AI use cases through scalable and governed data products.

Mandatory Skills :

- Databricks (Delta Lake, Unity Catalog, Databricks Workflows).

- Apache Spark, PySpark & SQL.

- Azure Data Platform & Cloud Architecture.

- Data Engineering (ETL/ELT, Data Modeling).

- Lakehouse Architecture & Enterprise Data Pipelines.

- Data Governance, Data Quality & Security.

Good-to-Have Skills :

- Azure DevOps, GitHub & CI/CD Pipelines.

- Terraform & Infrastructure as Code (IaC).

- Kubernetes & Container Technologies.

- Real-Time Data Processing / Streaming Solutions.

- Machine Learning & Generative AI Data Platforms.

- Databricks Professional Certifications.

Professional Experience & Qualifications :

- 8+ years of experience in Data Engineering, Data Platforms, Analytics, or Cloud Data Architecture.

- 3-5+ years of hands-on experience working with Databricks.

- Proven experience designing and implementing modern data platforms, large-scale data pipelines, and cloud-based analytics solutions.

- Strong knowledge of Azure data services, storage, networking, and security.

- Hands-on experience with DataOps methodologies, CI/CD pipelines, and platform automation.

- Strong understanding of data governance, lineage, metadata management, privacy, and compliance frameworks.

- Demonstrated experience leading technical teams and managing enterprise-scale data transformation initiatives.

- Excellent stakeholder management, communication, and problem-solving skills.

Skills

Data Architect, Azure Databricks, Data Quality, Spark, SQL, Data Modeling, ETL, Cloud, Data Engineering, Data Pipeline

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