Azure Data Engineer

Overview

Role: Azure Data Engineer

Location: Multiple location

Mode: Hybrid

Type: Permanent

Job Description:

We are seeking a highly skilled Azure Databricks Data Engineer to design, develop, and optimize data solutions on Azure. The ideal candidate will have expertise in Azure Data Factory (ADF), Databricks, SQL, Python, and experience working with SAP IS-Auto as a data source. This role involves data modeling, systematic layer modeling, and ETL/ELT pipeline development to enable efficient data processing and analytics.

Key Responsibilities:

• Develop & Optimize ETL Pipelines: Build robust and scalable data pipelines using ADF, Databricks, and Python for data ingestion, transformation, and loading.
• Data Modeling & Systematic Layer Modeling: Design logical, physical, and systematic data models for structured and unstructured data.
• Integrate SAP IS-Auto: Extract, transform, and load data from SAP IS-Auto into Azure-based data platforms.
• Database Management: Develop and optimize SQL queries, stored procedures, and indexing strategies to enhance performance.
• Big Data Processing: Work with Azure Databricks for distributed computing, Spark for large-scale processing, and Delta Lake for optimized storage.
• Data Quality & Governance: Implement data validation, lineage tracking, and security measures for high-quality, compliant data.
• Collaboration: Work closely with business analysts, data scientists, and DevOps teams to ensure data availability and usability.

Required Skills & Experience:

• Azure Cloud Expertise: Strong experience in Azure Data Factory (ADF), Databricks, and Azure Synapse.
• Programming: Proficiency in Python for data processing, automation, and scripting.
• SQL & Database Skills: Advanced knowledge of SQL, T-SQL, or PL/SQL for data manipulation.
• SAP IS-Auto Data Handling: Experience integrating SAP IS-Auto as a data source into data pipelines.
• Data Modeling: Hands-on experience in dimensional modeling, systematic layer modeling, and entity-relationship modeling.
• Big Data Frameworks: Strong understanding of Apache Spark, Delta Lake, and distributed computing.
• Performance Optimization: Expertise in query optimization, indexing, and performance tuning.
• Data Governance & Security: Knowledge of RBAC, encryption, and data privacy standards.

Preferred Qualifications:

• Experience with CI/CD for data pipelines using Azure DevOps.
• Knowledge of Kafka/Event Hub for real-time data processing.
• Experience with Power BI/Tableau for data visualization (not mandatory but a plus).

Job Type: Permanent

Pay: ₹3,000,000.00 - ₹3,700,000.00 per year

Benefits:

• Paid sick time
• Paid time off
• Work from home

Schedule:

• Day shift
• Monday to Friday

Supplemental Pay:

• Performance bonus

Experience:

• Azure Databricks: 4 years (Required)
• Data Engineering: 6 years (Required)
• SAP Industry Solution for Automotive (IS-Auto): 3 years (Required)

Work Location: Remote