Azure Data Engineer
ERP Logic Israel, SAP Partner · Bangalore, India ·
- Category
- Data engineering
- Experience
- 8+ years
- Company size
- 1000+
ERP Logic Israel, SAP Partner · Bangalore, India ·
weekday-1 · Mumbai, Maharashtra, India
aia · Kuala Lumpur, MY-AIA Malaysia
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Designs, builds, and maintains cloud data pipelines on Microsoft Azure — ingesting, transforming, and validating data into lakes and warehouses using Azure Data Factory, Databricks, PySpark, and SQL to power reporting, dashboards, and AI. Requires 8+ years of developer experience with strong hands-on Azure data engineering skills.
Company Description
ERP Logic is a globally recognized SAP Cloud Solutions company, specializing in SAP implementation and application services. Since its inception in 2009, the company has grown significantly to over 1,000 employees and expanded its presence across the United States, Europe, the Middle East, India, and Israel. As one of the top three SAP reseller partners globally for SAP S/4HANA Grow and SAP S/4HANA Rise, ERP Logic serves over 500 customers, including both large enterprises and mid-sized companies. With deep expertise in SAP S/4HANA and SAP ECC, ERP Logic supports businesses in transitioning to advanced ERP systems with a customer-centric approach and sustainable solutions.
Role Description
Azure Data Engineer will build and manage cloud data systems on Microsoft Azure. They will clean, transform, and move data into data lakes and warehouses using Microsoft Azure tools like Azure Data Factory, Databricks, and Synapse Analytics to support business analytics. This organized data is then used by business teams for reports, dashboards, and artificial intelligence.
Key Responsibilities
• Develop and support data engineering solutions using Azure Data Factory and Azure Databricks
• Build, enhance, and maintain data pipelines for ingestion, transformation, validation, and delivery
• Work on hands-on development activities across data acquisition, processing, and consumption layers
• Analyze functional specifications and user stories, and translate them into technical implementation tasks
• Develop scalable and reusable data processing logic using PySpark, SQL, and Databricks notebooks
• Create, schedule, monitor, and troubleshoot ADF pipelines, triggers, linked services, datasets, and integration runtimes
• Support data integration from multiple source systems into the data lake or data warehouse environment
• Perform unit testing, data validation, debugging, and defect resolution for data pipelines and transformation logic
• Monitor pipeline execution, investigate failures, and implement fixes to improve reliability and performance
• Participate in code reviews and follow agreed development standards, naming conventions, and best practices
• Work with business analysts, senior engineers, architects, and other team members to clarify requirements and deliver assigned development tasks
• Support automation and process improvement activities to improve data processing efficiency and accuracy
• Maintain technical documentation for pipelines, notebooks, data flows, and operational procedures
• Provide status updates on assigned tasks, highlight issues or blockers, and support timely resolution
• Work independently on assigned development activities while collaborating effectively within the team
• Stay willing and enthusiastic to learn new data engineering technologies, tools, and development practices
• Stay current with Azure data engineering technologies and continuously learn new tools, frameworks, and best practices
Required Education, Experience and Skill Set:
• Bachelor’s Degree in Information Systems, Computer Science or in a related field or equivalent work experience and practical knowledge
• Minimum 8+ years of experience as a Developer
• Experience in developing SQL, DataBricks/ DataLke required
• Minimum 3 years of experience in working with cross-functional teams preferred
• Strong hands-on development experience with Azure Data Factory (ADF) and Azure Databricks (ADB).
• Proficiency in Python, PySpark, Spark SQL, and SQL for data engineering development
• Experience developing, enhancing, and supporting enterprise-scale ETL/ELT data pipelines
• Good understanding of Azure data services, including ADLS Gen2, Azure Key Vault, Azure DevOps, and related cloud components
• Knowledge of Delta Lake, Medallion Architecture, and Data Lake concepts
• Understanding of data modeling, data quality, and data governance principles
• Experience with Git-based version control, branching, pull requests, and CI/CD practices
• Ability to perform unit testing, data validation, debugging, and production issue troubleshooting
• Strong analytical, problem-solving, and root-cause analysis skills
• Good communication and collaboration skills to work effectively with business analysts, architects, senior engineers, and cross-functional teams
• Understanding of machine learning libraries, genie space, agent bricks is an added advantage
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