Note: The job is a remote job and is open to candidates in USA. Precision Technologies is seeking an experienced Azure Data Engineer to design, build, and optimize large-scale data processing systems and pipelines on Microsoft Azure. The Senior Data Engineer will develop scalable data platforms, data warehouses, lakehouses, ETL/ELT workflows, streaming solutions, and analytics integrations while ensuring data quality, governance, security, and performance.
Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Azure Data Factory (ADF), Azure Databricks, and Azure Synapse Analytics to process and transform large volumes of structured and unstructured data
- Build and optimize big data processing solutions using Apache Spark, PySpark, Scala, or SQL within Azure Databricks, ensuring high performance and efficient data transformation
- Design and implement modern data warehouse and lakehouse architectures using Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), and Azure SQL Database to support enterprise-level analytics and reporting
- Develop and maintain data ingestion frameworks to integrate data from multiple sources such as databases, APIs, flat files, streaming platforms, and third-party applications into Azure-based data platforms
- Implement data modeling techniques including star schema, snowflake schema, and dimensional modeling to support business intelligence and analytical workloads
- Develop SQL-based data transformation and data quality validation processes using T-SQL, Spark SQL, and stored procedures to ensure accuracy, consistency, and reliability of data
- Integrate data engineering solutions with business intelligence and analytics tools such as Power BI, Tableau, or Azure Analysis Services for reporting and data visualization
- Implement real-time and streaming data processing solutions using Azure Event Hub, Azure Stream Analytics, or Apache Kafka to support near real-time analytics
- Optimize data storage, partitioning, indexing, and query performance across Azure-based data platforms to ensure efficient data retrieval and processing
- Implement data governance, security, and compliance using Azure Active Directory (AAD), Role-Based Access Control (RBAC), data encryption, and data masking techniques
- Automate deployment and data pipeline orchestration using CI/CD pipelines with Azure DevOps, GitHub Actions, or Jenkins, ensuring reliable and consistent deployment processes
- Monitor and troubleshoot data pipelines, workflows, and cloud resources using Azure Monitor, Log Analytics, and Application Insights to ensure system reliability and performance
- Collaborate with data architects, DevOps engineers, and cross-functional Agile teams to design scalable data engineering solutions aligned with enterprise data strategies
- Mentor junior data engineers and contribute to best practices in data engineering, cloud architecture, and performance optimization
Skills
- • 10+ Years of experience in data engineering
- • Cloud Platform: Microsoft Azure
- • Azure Data Services: Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), Azure SQL Database
- • Big Data Technologies: Apache Spark, PySpark, Scala, Spark SQL
- • Programming Languages: Python, SQL, Scala
- • Data Warehousing: Azure Synapse Analytics, Azure SQL Data Warehouse, Snowflake Concepts, Dimensional Modeling
- • ETL/ELT Tools: Azure Data Factory, Databricks Workflows
- • Streaming Technologies: Azure Event Hub, Azure Stream Analytics, Apache Kafka
- • Databases: SQL Server, Azure SQL Database, PostgreSQL, MySQL, NoSQL
- • Data Visualization Tools: Power BI, Tableau
- • Version Control: Git, GitHub, Bitbucket, GitLab
- • CI/CD Tools: Azure DevOps, Jenkins, GitHub Actions
- • Containerization: Docker, Kubernetes
- • Operating Systems: Windows, Linux
- • Methodologies: Agile, Scrum, DevOps, DataOps
- • Experience with data governance and compliance frameworks
Benefits
- Remote work arrangement
Company Overview
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