
Data Architect
2 weeks ago
We are seeking a skilled Data Engineer to build, optimize, and maintain data pipelines and architectures.
Key Responsibilities:- Design, develop, and optimize scalable data pipelines and workflows using Azure Data Factory, Synapse Pipelines, and Microsoft Fabric.
- Transform and migrate existing Alteryx workflows into scalable Azure Databricks pipelines, ensuring optimized performance and maintainability.
- Collaborate with data engineering and analytics teams to redesign Alteryx pipelines into Spark-based solutions on Azure Databricks, leveraging Delta Lake and Azure services for automation and efficiency.
- Build and maintain ETL/ELT processes for ingesting structured and unstructured data from various sources.
- Develop and manage data transformation logic using Databricks (Py Spark/SparkSQL) and Python.
- Collaborate with data analysts, architects, and business stakeholders to understand requirements and deliver high-quality data solutions.
- E nsure data quality, integrity, and governance across the data lifecycle.
- Implement monitoring and alerting for data pipelines to ensure reliability and performance.
- Work with Azure Synapse Analytics to build data models and enable analytics and reporting.
- Utilize SQL for querying and managing large datasets efficiently.
As a Data Engineer at our company, you will have the opportunity to work on cutting-edge projects, collaborate with a talented team, and develop your skills in data engineering.
Benefits:- Competitive salary and benefits package
- Opportunities for professional growth and development
- Collaborative and dynamic work environment
- Bachelor's degree in Computer Science, Engineering, or related field
- Minimum 5 years of experience in data engineering
- Proficiency in Azure Data Factory, Synapse Pipelines, and Microsoft Fabric
- Experience with Py Spark/SparkSQL and Python
We are a leading provider of data engineering solutions. Our team is passionate about delivering high-quality data solutions that meet the needs of our clients.
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