Data Engineer
Redmond, WA, United States
WaferWire is currently seeking a Data Engineer to join its innovative team.
Role: Data Engineer
Location: Redmond, WA
Job Description:
Key Responsibilities:
Design, develop, and maintain robust data pipelines using Microsoft SQL Server and Azure Data Factory.
Implement ETL processes to consolidate data from various sources into a centralized data warehouse.
Optimize and troubleshoot SQL queries, stored procedures, and database performance.
Develop, deploy, and manage data models and reports using Power BI.
Collaborate with business stakeholders to understand their data requirements and deliver actionable insights.
Ensure data quality, integrity, and security across all data assets.
Monitor and maintain data systems to ensure high availability and performance.
Document data processes, architectures, and environments for future reference and training.
Stay updated with the latest trends and best practices in data engineering and business intelligence.
Qualifications:
Bachelor's degree in Computer Science, Information Technology, or a related field.
Proven experience in data engineering, with a focus on cloud platforms and Microsoft technologies.
3+ years of experience as a Data Engineer or in a similar role.
Strong proficiency in Microsoft SQL Server, including T-SQL, SSIS, and SSRS.
Hands-on experience with Azure Data Services (Azure Data Factory, Azure SQL Database, Azure Synapse Analytics).
Expertise in KQL, Power BI, including data modeling, DAX, Power Query, Power BI Service and report/dashboard development.
Familiarity with data warehousing concepts and technologies.
Experience with scripting languages such as Python or PowerShell is a plus.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills, with the ability to work effectively in a team environment.
Preferred Skills:
Experience with Azure DevOps for CI/CD in data projects.
Knowledge of other BI tools and platforms.
Understanding of machine learning and data science principles.
Experience with big data technologies like Azure Data Lake, Databricks, or Hadoop.
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