Azure Data Architect

19 hours ago

Dombivli, Maharashtra, India beBeeDataEngineer Full time ₹ 12,00,000 - ₹ 21,00,000
Data Engineer – Azure Platform

We are seeking a skilled Data Engineer to play a critical role in designing, developing, and managing data pipelines and transformation frameworks that enable analytics, reporting, and business intelligence capabilities across the enterprise.

You will be working closely with data architects, platform engineers, and DevOps teams to build scalable, resilient, and efficient data engineering solutions using modern Azure tools and best practices. The ideal candidate will have hands-on experience with Azure Data Factory, Databricks, Synapse Analytics, Apache Kafka, SQL, Python, and Spark for data manipulation and transformation.

The successful candidate will also possess strong problem-solving skills, attention to detail, and excellent communication and collaboration skills. They will be able to design and build scalable ETL/ELT pipelines, develop and optimize PySpark/Spark SQL jobs, ingest data from various sources, implement data modeling strategies, and monitor, troubleshoot, and optimize data workflows.

Key Responsibilities:
  • Design and build scalable ETL/ELT pipelines using Azure Data Factory (ADF), Databricks (Spark), and 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.
Required Skills and Qualifications:
  • 5+ years of experience in data engineering roles.
  • Hands-on experience with:
    Azure Data Factory (ADF) – building pipelines, triggers, linked services.
    Azure Databricks – building and managing Spark jobs in PySpark.
    Azure Synapse Analytics – data warehousing, SQL queries, workspace orchestration.
    Apache Kafka – consuming and processing real-time data streams.
  • Strong in SQL, Python, and Spark for data manipulation and transformation.
  • Exposure to CI/CD practices (Azure DevOps, Git workflows, build/release pipelines).
  • Understanding of data lake architecture and modern data warehousing principles.
Preferred Certifications:
  • Microsoft Certified: Azure Data Engineer Associate
  • Databricks Certified Associate Developer for Apache Spark
  • Azure Fundamentals (AZ-900) – optional but helpful

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