8 years

0 Lacs

Posted:2 days ago| Platform: Linkedin logo

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Contractual

Job Description

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We are seeking an experienced Azure Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions on the Microsoft Azure platform. The ideal candidate will have strong hands-on expertise in Azure Data Factory (ADF), Azure Databricks, and Power BI, and will work closely with business stakeholders, data analysts, and data scientists to enable data-driven decision-making.


Responsibilities:

  • Data Engineering & Pipeline Development
  • Design, develop, and maintain end-to-end ETL/ELT pipelines using Azure Data Factory (ADF).
  • Ingest data from multiple sources (databases, APIs, flat files, streaming sources) into Azure data platforms.
  • Implement data transformations using Azure Databricks (PySpark / Spark SQL).
  • Build and optimize data solutions using Azure Data Lake Storage (ADLS Gen2) and/or Azure Synapse Analytics.
  • Ensure data quality, data validation, and schema enforcement.
  • Implement partitioning, performance tuning, and cost optimization strategies.
  • Collaborate with BI teams to model data for reporting and analytics.
  • Support and optimize datasets consumed by Power BI dashboards and reports.
  • Implement incremental refresh, row-level security (RLS), and performance best practices in Power BI.
  • Automate workflows and scheduling using ADF triggers and pipelines.
  • Monitor pipeline performance, failures, and data latency; troubleshoot and resolve issues.
  • Implement data security, access control, and governance aligned with Azure best practices.
  • Work closely with business analysts, data scientists, and application teams.
  • Document data pipelines, architecture, and operational procedures.
  • Participate in design reviews, code reviews, and continuous improvement initiatives.


Requirements:

  • Strong experience with Azure Data Factory (ADF) – pipelines, triggers, integration runtimes.
  • Hands-on expertise in Azure Databricks with PySpark / Spark SQL.
  • Experience building datasets and reports for Power BI.
  • Solid understanding of data warehousing concepts (star schema, slowly changing dimensions).
  • Proficiency in SQL for data analysis and transformations.
  • Experience with Azure Data Lake Storage (ADLS Gen2).
  • Experience with Azure Synapse Analytics.
  • Knowledge of CI/CD pipelines using Azure DevOps or GitHub Actions.
  • Exposure to Delta Lake, data versioning, and optimization techniques.
  • Experience with streaming data (Event Hub / Kafka) is a plus.
  • Familiarity with Python beyond Spark (for utilities, automation).

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