Job Title      : Data Engineer 
Experience  : 7-10 Years
Location      : Remote

Job Description :

Key Responsibilities:

• Schema Design & Data Modeling:
  • Design normalized, denormalized, star, and snowflake schemas based on business requirements.
  • Optimize database structures to enhance performance and scalability.
  • Implement partitioning, indexing, and clustering strategies for efficient data retrieval.
• Data Engineering & ETL/ELT Pipelines:
  • Develop and maintain ETL/ELT processes using Azure Data Factory (ADF), Databricks, and Synapse Analytics.
  • Ensure efficient data ingestion, transformation, and storage in Azure Data Lake, SQL Database, and Synapse.
  • Work with structured and unstructured data, optimizing data flows for analytical processing.
• Cloud Data Architecture & Optimization:
  • Design and implement scalable Azure-based data architectures.
  • Utilize Azure Data Lake, Cosmos DB, Synapse Analytics, and SQL Server for data storage and processing.
  • Implement data partitioning, indexing, and caching strategies to optimize query performance.
• Good Communication skills.

Required Skills & Experience:

• 8+ years of experience in data engineering, with a focus on schema design and data modeling.
• Strong expertise in Azure Data Services (Azure Data Lake, Azure Synapse Analytics, Azure SQL Database, Cosmos DB, Databricks, Azure Data Factory).
• Hands-on experience in schema design principles (OLTP vs. OLAP, star/snowflake schema, indexing, partitioning).
• Proficiency in SQL, Python, or Scala for data processing and transformation.
• Experience with Big Data processing using Apache Spark, Delta Lake, and Parquet formats.
• Knowledge of data governance, security, and compliance best practices would be an added plus.
• Familiarity with CI/CD pipelines for data workflows using Azure DevOps.
• Experience in performance tuning, query optimization, and cost management on Azure.