Senior Data Engineer

6 days ago

Yelahanka, Karnataka, India GeekSoft Consulting Full time ₹ 15,00,000 - ₹ 20,00,000 per year
  • Help design, build and continuously improve the clients online platform.
  • Research, suggest and implement new technology solutions following best practices/standards.
  • Take responsibility for the resiliency and availability of different products.
  • Be a productive member of the team.


Requirements Key Responsibilities:
  • Analyze and document current data integration approaches, including FTP/PowerShell scripts, InfoHub SQL, and Azure Data Factory (ADF).
  • Map and document data flow dependencies, transformation logic, and data consumption patterns in Databricks and Power BI.
  • Design and implement standardized, scalable data pipelines using Azure Data Factory.
  • Develop efficient ingestion mechanisms for SAP (Vision), including support for future enhancements such as incremental or event-driven data loading.
  • Review and refine transformation logic, promoting architectural best practices such as the medallion (bronze/silver/gold) model.
  • Implement and maintain incremental data load strategies and Change Data Capture (CDC) processes.
  • Develop robust monitoring, logging, and alerting systems to ensure data pipeline reliability and performance.

Required Qualifications:
  • 5–7 years of hands-on data engineering experience, with 2–3 years specifically using Azure Databricks.
  • Advanced SQL skills, including complex joins, common table expressions (CTEs), and analytical functions.
  • Proven experience in ETL/ELT development using Databricks with PySpark, SQL, or Scala.
  • Strong understanding of Delta Lake features such as ACID transactions, time travel, version control, and schema evolution.
  • Experience integrating SAP data using ADF, APIs, or CDC strategies.
  • Solid grasp of dimensional data modeling and medallion architecture principles.
  • Proficiency with Azure services such as Azure Data Lake Storage (ADLS), Azure Data Factory, and Azure Key Vault.
  • Familiarity with Git-based CI/CD processes and collaborative development using tools like Databricks Repos.
  • Experience implementing data quality validation, logging, and monitoring frameworks.


Benefits
  • A challenging, innovating environment.
  • Opportunities for learning where needed.

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