Note: The job is a remote job and is open to candidates in USA. Datavail is a provider of data management, application development, analytics, and cloud services. The company is seeking an Azure Data Engineer to design, develop, and optimize enterprise-scale data platforms using Azure and Snowflake. The role is responsible for building data pipelines, managing data warehouses and lakes, implementing governance and security, supporting cloud modernization, and resolving production data challenges.
Responsibilities
- Design, develop, and maintain scalable data engineering solutions on Azure and Snowflake platforms
- Build and optimize ETL/ELT pipelines using Azure Data Factory, Databricks, and Snowflake to ingest, transform, and load data from various structured and unstructured sources
- Develop and maintain enterprise data warehouses, data marts, and analytical datasets supporting reporting, BI, and advanced analytics initiatives Implement data transformation and orchestration processes using PySpark, SQL, Python, and Snowflake stored procedures
- Design and manage cloud-based data lakes using Azure Data Lake Storage (ADLS Gen2) and Delta Lake architecture
- Collaborate with business stakeholders, data analysts, and architects to gather requirements and translate them into scalable data solutions
- Monitor and optimize data pipeline performance, ensuring reliability, scalability, and cost efficiency
- Implement data quality frameworks, validation rules, and monitoring processes to ensure accurate and trusted data
- Manage Snowflake objects including databases, schemas, warehouses, tasks, streams, and data-sharing capabilities
- Develop and maintain dimensional and normalized data models following industry best practices
- Implement security controls, access management, encryption, and governance policies across Azure and Snowflake environments
- Support cloud migration and modernization initiatives from on-premises or legacy platforms to Azure and Snowflake
- Automate deployment processes using Azure DevOps, Git repositories, and CI/CD pipelines
- Troubleshoot production issues, perform root cause analysis, and provide timely resolution for data-related challenges
- Participate in Agile ceremonies, code reviews, and technical design discussions to ensure high-quality solution delivery
- Create technical documentation, architecture diagrams, operational runbooks, and knowledge-transfer materials
Skills
- Azure Data Engineer with 6+ years of experience designing, developing, and optimizing enterprise-scale data platforms using Microsoft Azure and Snowflake
- Proven expertise in building scalable data pipelines, data warehouses, and analytics solutions leveraging Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, Snowflake, Python, SQL, and Spark
- Experienced in data modeling, ETL/ELT development, cloud migration, performance tuning, data governance, and implementing CI/CD practices
- Strong background in integrating data from multiple sources and enabling business intelligence and advanced analytics solutions
- Azure Data Factory (ADF)
- Azure Databricks
- Azure Synapse Analytics
- Snowflake Data Cloud
- Python, PySpark, SQL
- Azure Data Lake Storage (ADLS Gen2)
- Azure Functions
- Delta Lake
- Data Warehousing & Data Modeling
- ETL / ELT Development
- CI/CD (Azure DevOps, Git)
- Performance Tuning & Optimization
- Data Governance & Security
- Power BI Integration
- Agile & Scrum Methodologies
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- SnowPro Core Certification
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