বিষয়বস্তুতে যান

Azure Lead Data Engineer

Overview
EXLexlservice.comPosted 5 weeks ago
Gurugram, Haryana, INঅফিসে
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জ্যেষ্ঠতার স্তর
Senior
চাকরির ধরন
পূর্ণকালীন
কাজের অভিজ্ঞতা
8+ years
বিশেষায়ন
Data engineering

Responsibilities

  • Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
  • Build and maintain data integration workflows from various data sources to Snowflake.
  • Write efficient and optimized SQL queries for data extraction and transformation.
  • Work with stakeholders to understand business requirements and translate them into technical solutions.
  • Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
  • Maintain and enforce data quality, governance, and documentation standards.
  • Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment.

Requirements

  • Strong experience with Azure Cloud Platform services.
  • Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines.
  • Proficiency in SQL for data analysis and transformation.
  • Hands-on experience with Snowflake and SnowSQL for data warehousing.
  • Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse.
  • Experience working in cloud-based data environments with large-scale datasets.
  • Experience with DataStage, Netezza,Azure Data Lake, Azure Synapse, or Azure Functions.
  • Familiarity with Python or PySpark for custom data transformations.
  • Understanding of CI/CD pipelines and DevOps for data workflows.
  • Exposure to data governance, metadata management, or data catalog tools.
  • Knowledge of business intelligence tools (e.g., Power BI, Tableau) is a plus.
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • 8+ years of experience in data engineering roles using Azure and Snowflake.
  • Strong problem-solving, communication, and collaboration skills.

Key skills

  • ETL
  • Azure
  • Snowflake
  • dbt
  • SQL
  • DevOps
  • Data Analysis
  • Data Warehousing
  • Python
  • Apache Spark
  • CI/CD
  • Power BI
  • Tableau
  • Data Engineering