Data Engineering Specialist

2 days ago

Thoothukudi, Tamil Nadu, India beBeeData Full time ₹ 17,50,000 - ₹ 22,50,000
Job Title

A Data Engineer is responsible for designing, building, and maintaining robust data platforms.

  • Key Responsibilities:
  • Data Pipeline Development: Create and manage jobs, dataflows, and triggers in Azure Data Factory and Azure Synapse Pipelines to ingest, transform, and load data from various sources into the Azure data platform.
  • Data Modeling and Warehousing: Develop conceptual, logical, and physical data models for data warehouses and data lakes using techniques such as star schema and snowflake schema.
  • Data Lake Management: Manage data storage and organization within Azure Data Lake Storage Gen2, ensuring proper folder structures, security, and data lifecycle management for raw, processed, and curated data zones.
  • Data Transformation: Utilize dbt (data build tool) to transform raw data into analytics-ready datasets by writing complex SQL queries and stored procedures to cleanse, enrich, and aggregate data.
  • Azure Service Integration: Integrate and work with a variety of Azure services, including Azure Synapse Analytics, Azure Databricks, Azure Functions, and Cosmos DB, to build a comprehensive data solution.
  • ETL/ELT Processes: Implement and optimize Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes to ensure data is moved efficiently and accurately.
  • Security and Governance: Apply data security best practices, implementing Role-Based Access Control (RBAC), managed identities, and Azure Key Vault to protect sensitive data. Work with Microsoft Purview for data cataloging and governance.
  • Performance Optimization: Monitor and optimize the performance of data pipelines, queries, and data warehouse solutions, fine-tuning data structures and processing logic to improve efficiency and reduce costs.

Requirements:

  • 4+ years of experience with key Azure data services, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure Databricks.
  • Strong proficiency in SQL and at least one programming language such as Python or Spark (PySpark, Scala).
  • Solid understanding of data warehousing principles, data modeling (dimensional modeling, etc.), and ETL/ELT concepts.
  • CI/CD: Experience with version control systems like Git and Continuous Integration/Continuous Deployment (CI/CD) practices using Azure DevOps.
  • Ability to work effectively with cross-functional teams to understand requirements and deliver data solutions.
  • Excellent analytical and problem-solving skills with a focus on delivering high-quality, reliable data solutions.
  • Strong verbal and written communication skills to articulate technical concepts to both technical and non-technical stakeholders.

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