We are looking for a Data Engineer to build, enhance, and support scalable data solutions on Azure. The role involves developing data pipelines, integrating SAP and non-SAP source systems, implementing data transformations in Databricks, and delivering trusted datasets for reporting, analytics, and business intelligence.
Key responsibilities
Data ingestion & integration
- Develop and maintain data ingestion pipelines using Azure Data Factory (ADF).
- Integrate data from SAP, databases, APIs, flat files, and cloud applications.
- Implement incremental and CDC-based data loading patterns.
- Troubleshoot data integration and pipeline issues.
Data transformation & processing
- Develop PySpark and SQL-based transformations in Azure Databricks.
- Build and maintain Bronze, Silver, and Gold layer datasets.
- Cleanse, validate, and enrich data to meet business requirements.
- Optimize jobs for performance, scalability, and cost efficiency.
Data warehousing & modeling
- Support implementation of enterprise data models and Common Data Models (CDM).
- Develop curated datasets for reporting and analytics.
- Ensure data consistency across multiple business domains.
Analytics enablement
- Deliver trusted datasets for Power BI and self-service analytics.
- Work closely with Business Analysts, BI Developers, and Data Architects to understand data requirements.
- Support report and dashboard performance improvements.
Governance & quality
- Implement data quality checks and validation frameworks.
- Adhere to data governance standards and security policies.
- Document data flows, business rules, and technical processes.
Support & operations
- Monitor scheduled jobs and data pipelines.
- Investigate and resolve production incidents.
- Perform root cause analysis and implement corrective actions.
- Participate in deployment and release activities.
Requirements
Preferred skills
- SAP ECC / SAP S/4HANA data integration
- REST API integrations
- Event-driven architectures
- Unity Catalog
- Microsoft Fabric
- Retail or Automotive domain experience
Experience
- Overall 5-8 years of experience , 3-6 years of Data Engineering experience.
- 2+ years of experience with Azure Databricks.
- 2+ years of experience with Azure Data Factory.
- Experience building enterprise-scale cloud data pipelines.
Technical skills
- Azure Data Factory (ADF)
- Azure Databricks
- Python and PySpark
- SQL
- Azure Data Lake Storage (ADLS)
- Delta Lake
Data engineering concepts
- ETL / ELT development
- Data warehousing
- Medallion Architecture
- Incremental loading
- Data modeling
- Data quality management
Reporting & analytics
- Power BI
- Dataset optimization
- Dimensional modeling
Version control & devops
- Git
- Azure DevOps
- CI/CD concepts
Education
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.