Azure Data Engineering Manager

Manager - Developer (Jr Developer DataBricks)

 Roles & responsibilities 
Role Overview: 
The Manager – Azure Data Engineer will lead a large team of data engineers, driving strategic initiatives in the Audit Data & Analytics domain. This role demands strong leadership qualities, deep technical expertise in Azure, and  ERP knowledge. The Manager will be responsible for delivering complex data solutions, ensuring operational excellence, and fostering a culture of collaboration and innovation.

Key Responsibilities:

Technical Delivery 
Perform and oversee data transformation and integration projects using Azure Databricks, Azure Data Factory, and Python/PySpark.
Design and manage scalable data processing pipelines and workflows to support analytics and audit requirements.
Apply advanced concepts such as partitioning, optimization, and performance tuning for efficient data processing.
Drive integration of ERP systems (SAP, Oracle, Microsoft Dynamics) with Azure-based solutions.
Debug, optimize, and resolve issues in large-scale data workflows, proposing effective solutions with minimal guidance.

Data Handling & Workflow Development

Demonstrate advanced knowledge of Azure cloud services, including Azure Databricks, Data Factory, Data Lake Storage, and related technologies.
Utilize tools such as Alteryx and PowerBI for data analysis and visualization.
Apply understanding of audit processes, financial data structures, and risk assessment routines.
Explore and apply Azure AI services to enhance business processes.

Resolve issues with minimal guidance and propose effective solutions.

Performance Optimization & Debugging

Debug, optimize, and tune performance for large-scale data processing workflows.
Resolve issues with minimal guidance and propose effective solutions.

Stakeholder Engagement

Act as a primary point of contact for audit engagement teams and client IT teams.
Communicate effectively with business leaders, translating technical solutions into business value.
Build strong relationships across global teams to enable seamless delivery

Domain Expertise (Added advantage)

Experience with General Ledger/Sub-Ledger analysis and development of risk assessment or substantive routines for Audit/Internal Audit (Big 4 experience preferred).

Additional Skills

Working knowledge of KQL (Kusto Query Language) and Azure REST APIs is a plus.
Enthusiasm to explore and apply Azure AI services in business processes.

 Roles & responsibilities 
Role Overview: 
The Manager – Azure Data Engineer will lead a large team of data engineers, driving strategic initiatives in the Audit Data & Analytics domain. This role demands strong leadership qualities, deep technical expertise in Azure, and  ERP knowledge. The Manager will be responsible for delivering complex data solutions, ensuring operational excellence, and fostering a culture of collaboration and innovation.

Key Responsibilities:

Technical Delivery 
Perform and oversee data transformation and integration projects using Azure Databricks, Azure Data Factory, and Python/PySpark.
Design and manage scalable data processing pipelines and workflows to support analytics and audit requirements.
Apply advanced concepts such as partitioning, optimization, and performance tuning for efficient data processing.
Drive integration of ERP systems (SAP, Oracle, Microsoft Dynamics) with Azure-based solutions.
Debug, optimize, and resolve issues in large-scale data workflows, proposing effective solutions with minimal guidance.

Data Handling & Workflow Development

Demonstrate advanced knowledge of Azure cloud services, including Azure Databricks, Data Factory, Data Lake Storage, and related technologies.
Utilize tools such as Alteryx and PowerBI for data analysis and visualization.
Apply understanding of audit processes, financial data structures, and risk assessment routines.
Explore and apply Azure AI services to enhance business processes.

Resolve issues with minimal guidance and propose effective solutions.

Performance Optimization & Debugging

Debug, optimize, and tune performance for large-scale data processing workflows.
Resolve issues with minimal guidance and propose effective solutions.

Stakeholder Engagement

Act as a primary point of contact for audit engagement teams and client IT teams.
Communicate effectively with business leaders, translating technical solutions into business value.
Build strong relationships across global teams to enable seamless delivery

Domain Expertise (Added advantage)

Experience with General Ledger/Sub-Ledger analysis and development of risk assessment or substantive routines for Audit/Internal Audit (Big 4 experience preferred).

Additional Skills

Working knowledge of KQL (Kusto Query Language) and Azure REST APIs is a plus.
Enthusiasm to explore and apply Azure AI services in business processes.

Mandatory  technical & functional skills
Proficiency in Azure, DataBricks Notebooks, SQL,  Python or Pyspark notebooks development.
Knowledge on any ERP and about the dataflows in ERP
Strong knowledge of ETL tools and processes.
Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS)
Comprehensive knowledge of Azure cloud services.
Experience with Databricks notebooks for building transformations and creating tables

 This role is for you if you have  the below
Educational qualifications 
B. Tech/B.E/MCA (Computer Science / Information Technology)

Work experience
Minimum 8-12 years of experience in data engineering, with deep expertise in Azure technologies.

 

 

Experience Level

Entry Level