Chief Data Transformation Specialist

16 hours ago

Aligarh, Uttar Pradesh, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Job Opportunity:

We seek a Data Engineering Specialist to contribute to the design, development, and management of data pipelines and transformation frameworks. These solutions will enable analytics, reporting, and business intelligence capabilities across our organization.

The ideal candidate will possess hands-on experience in Microsoft Azure data tools and collaborate with data architects, platform engineers, and DevOps teams to build scalable, resilient, and efficient data engineering solutions using modern Azure best practices.

  • Key Responsibilities:
  • Design and implement scalable ETL/ELT pipelines using Azure Data Factory (ADF), Azure Databricks (Spark), and Azure Synapse Analytics.
  • Develop and optimize PySpark/Spark SQL jobs for large-scale batch and streaming data transformations.
  • Ingest data from various sources, including Apache Kafka, REST APIs, and RDBMS, ensuring real-time or near-real-time availability.
  • Implement data modeling strategies (star schema, snowflake schema) for analytics consumption layers in Synapse or ADLS.
  • Collaborate with DevOps teams to automate deployment using CI/CD pipelines (Azure DevOps, GitHub Actions, etc.).
  • Monitor, troubleshoot, and optimize data workflows for performance, cost-efficiency, and reliability.
  • Follow coding standards, participate in peer reviews, and maintain version-controlled code in Git repositories.
  • Support data quality checks, logging, alerting, and observability mechanisms for production workloads.
  • Participate in sprint ceremonies and contribute to task estimation and delivery planning.

Required Skills:

Hands-on experience with Azure Data Factory (ADF), Azure Databricks (Spark), and Azure Synapse Analytics.

Strong proficiency in SQL, Python, and Spark for data manipulation and transformation.

Exposure to CI/CD practices (Azure DevOps, Git workflows, build/release pipelines).

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