Chief Data Engineering Specialist

1 day ago

Tiruchi, Tamil Nadu, India beBeeData Full time ₹ 80,00,000 - ₹ 1,20,00,000
Senior Data Engineer Opportunity

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.

The ideal candidate will work closely with data architects, platform engineers, and DevOps teams to build scalable, resilient, and efficient data engineering solutions using modern tools and best practices.

Key Responsibilities:

  • Create and maintain large-scale data pipelines using Azure Data Factory (ADF), Azure Databricks (Spark), and Azure Synapse Analytics.
  • Develop and optimize PySpark/Spark SQL jobs for batch and streaming data transformations.
  • Ingest data from various sources including Apache Kafka, REST APIs, and RDBMS, ensuring 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.
  • Monitor, troubleshoot, and optimize data workflows for performance, cost-efficiency, and reliability.
  • Foster a culture of excellence by adhering to coding standards, participating in peer reviews, and maintaining 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.

Requirements:

  • 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.

Bonus Skills:

  • Experience with Delta Lake, Event Hub, or Azure Stream Analytics.
  • Familiarity with infrastructure-as-code tools like Terraform or ARM templates.
  • Exposure to Data Governance, Data Quality frameworks, or metadata management.
  • Understanding of networking, security, and access control in Azure data services.

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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