Data Engineer

2 days ago

vadodara, India Kiash Solutions LLP Full time

1. Data Architecture Design      Design end-to-end data architectures using Azure services (e.g., Azure Synapse Analytics, Azure Data Lake, Azure SQL Database, Cosmos DB).      Define data models, data flows, and integration patterns aligned with business and technical requirements.      Ensure solutions support scalability, reliability, and performance goals. 2. Data Integration and ETL/ELT      Design and oversee data ingestion pipelines using tools like Azure Data Factory, Synapse Pipelines, or Databricks.      Establish processes for data transformation, cleansing, and enrichment.      Integrate structured, semi-structured, and unstructured data from multiple sources (on-premises and cloud). 3. Data Storage and Management      Choose appropriate storage solutions (e.g., Data Lake Gen2, Blob Storage, SQL, Cosmos DB) based on use cases.      Define data retention policies, partitioning strategies, and lifecycle management.      Optimize storage performance and cost. 4. Data Governance and Security      Implement data governance frameworks, including data lineage, cataloging, and metadata management (e.g., Azure Purview / Microsoft Purview).      Ensure compliance with GDPR, HIPAA, and other regulations.      Define and implement data security, encryption, and role-based access control (RBAC) in Azure. 5. Analytics and BI Enablement      Architect analytical environments for Power BI, Azure Synapse, and Databricks.      Enable real-time and batch analytics.      Ensure that data is accessible and trustworthy for reporting and machine learning. 6. Collaboration and Stakeholder Management      Work with data engineers, analysts, scientists, and business stakeholders to understand data requirements.      Translate business goals into technical data strategies.      Provide architectural guidance to cross-functional teams. 7. Performance Optimization      Monitor and optimize query performance, data pipelines, and storage costs.      Implement data partitioning, caching, and indexing strategies.      Use Azure Monitor, Log Analytics, and other tools for system health and performance tracking. 8. Cloud Strategy and Best Practices      Develop and maintain a data strategy aligned with overall Azure cloud architecture.      Stay current on Azure updates and industry trends to recommend improvements.      Promote DevOps and CI/CD practices for data pipeline deployment and management. 9. Documentation and Standards      Create and maintain architecture diagrams, design documents, and data dictionaries.      Define naming conventions, coding standards, and documentation best practices for data teams. 10. Mentorship and Leadership      Guide and mentor data engineers and developers in best practices for Azure data solutions.      Provide architectural oversight during project execution.      Conduct code and design reviews to ensure consistency and quality.

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