Role Summary:

The Azure Data Engineering Manager will lead the design, architecture, and implementation of enterprise-scale data platforms using Microsoft Azure, Microsoft Fabric, and Databricks. The role combines hands-on technical expertise, solution architecture, delivery leadership, client engagement, and presales support for modern Data Warehouse, Lakehouse, and Analytics solutions.

Roles & Responsibilities:

- Design, architect, and lead the implementation of scalable data platforms and analytics solutions using Microsoft Fabric, Databricks, and Azure services.

- Lead the development of batch, streaming, and near real-time data pipelines for ingestion, transformation, and analytics.

- Define architecture standards, reusable frameworks, and best practices for data engineering, governance, security, performance optimization, and operational excellence.

- Provide hands-on technical guidance and support teams in resolving complex data engineering, performance, scalability, and platform challenges.

- Drive Data Warehousing, Lakehouse architecture, data modeling, metadata-driven ingestion, data quality, and governance initiatives.

- Manage project planning, estimation, delivery risks, dependencies, quality, and stakeholder communication.

- Mentor and develop data engineering teams, fostering technical excellence, collaboration, and continuous learning.

- Partner with client stakeholders to translate business requirements into scalable architecture and delivery roadmaps.

- Support business development and presales activities, including solution design, effort estimation, RFP/RFI responses, proposal development, technical workshops, client presentations, and demonstrations.

Required Experience & Skills:

- Minimum 10+ years of Data Engineering experience, including experience leading enterprise-scale Azure data platform implementations.

Technical & Architecture Skills:

- Strong hands-on experience with Microsoft Fabric and Databricks, including Lakehouse Architecture, Medallion Architecture, OneLake, Delta Lake, Fabric Data Factory, Fabric Notebooks, and Databricks Workflows.

- Strong proficiency in PySpark, Spark SQL, Delta Lake, and distributed data processing frameworks.

- Experience designing and implementing scalable ETL/ELT solutions using Microsoft Fabric, Databricks, Azure Data Factory, Synapse Analytics, Azure Functions, and related Azure services.

- Experience building metadata-driven ingestion, orchestration, and data quality frameworks.

- Experience handling streaming and near real-time datasets using Spark Structured Streaming, Event Hub, Kafka, or similar technologies.

- Strong expertise in Data Modeling, Dimensional Modeling, Enterprise Data Warehousing, and Lakehouse design.

- Strong understanding of Unity Catalog, data governance, lineage, Azure RBAC, IAM, security, and compliance controls.

- Ability to troubleshoot complex performance, scalability, and distributed processing challenges.

Leadership, Delivery & Consulting Skills:

- Experience leading and mentoring data engineering teams while driving engineering best practices and delivery excellence.

- Proven experience managing business stakeholders, solution architects, delivery teams, and client leadership.

- Strong consulting and client-facing delivery experience with enterprise data and analytics programs.

- Experience delivering enterprise-scale Data & Analytics initiatives and managing multiple workstreams across distributed teams.

- Experience supporting business development initiatives through solutioning, RFP/RFI responses, effort estimation, proposal preparation, technical workshops, and client presentations.

- Strong communication and presentation skills with the ability to effectively engage both technical and business stakeholders.

Good to Have:

- Experience with Spark performance tuning, Delta Lake optimization, workload management, and cloud cost optimization.

- Experience with Azure DevOps, Git, CI/CD pipelines, and release management.

- Exposure to Microsoft Copilot, Generative AI, and AI-enabled data engineering use cases.

- Power BI experience, including semantic models, dashboards, and KPI reporting.

- Relevant Microsoft certifications (DP-600, DP-700, DP-203, DP-900, AI-102, AI-900) and/or Databricks certifications.

- Experience delivering consulting engagements within global or distributed delivery models.

Location:

- Bangalore / Pune / Hyderabad