Data Engineer

Manager

     Roles & responsibilities 
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, people management and delivery 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:

Leadership & Team Management
Lead and manage a team of 10–16 data engineers, ensuring high performance and engagement.
Set clear goals, monitor progress, and provide coaching and mentorship to team members.
Foster an inclusive and collaborative environment that promotes knowledge sharing and continuous improvement.
Manage resource allocation, workload balancing, and succession planning and execution
Delivery with quality deliverables and timely

Technical Delivery 
Design and manage scalable data processing pipelines and workflows to support analytics and audit requirements.
Perform and oversee data transformation and integration projects using Azure Databricks, Azure Data Factory, and Python/PySpark.
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.
working experience and certification MS Fabric as Data analytics is preferred

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 .

 

Roles & responsibilities 
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, people management and delivery 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:

Leadership & Team Management
Lead and manage a team of 10–16 data engineers, ensuring high performance and engagement.
Set clear goals, monitor progress, and provide coaching and mentorship to team members.
Foster an inclusive and collaborative environment that promotes knowledge sharing and continuous improvement.
Manage resource allocation, workload balancing, and succession planning and execution
Delivery with quality deliverables and timely

Technical Delivery 
Design and manage scalable data processing pipelines and workflows to support analytics and audit requirements.
Perform and oversee data transformation and integration projects using Azure Databricks, Azure Data Factory, and Python/PySpark.
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.
working experience and certification MS Fabric as Data analytics is preferred

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 .

Mandatory  technical & functional skills
Proficiency in Azure, Data Bricks 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
Experience in Alteryx and PowerBI for data analysis and visualization purpose.
Microsoft Fabric and Azure AI services is an added advantage
Understanding of audit processes, financial data structures, and risk assessment routines.

This role is for you if you have  the below
Educational qualifications 
B. Tech/B.E/MCA (CSIT/ ME/ EEE/EC)

Work experience
Minimum 7-9 years of experience in data engineering, with deep expertise in Azure technologies.
Minimum 3–4 years of experience leading medium teams (10+ members).

Experience Level

Mid Level