Power Automate Data Engineer

Role: Data Engineer with Power Automate

Location: London (preferred), open to Birmingham, Manchester, or Newcastle

Duration: 6+ months contract

Mandatory: Power Automate Experience & Databricks

A "Data Engineer with Power Automate" job description would typically seek a candidate with strong data engineering skills, including data extraction, transformation, and loading (ETL), combined with proficiency in using Microsoft Power Automate to automate data workflows and processes within a business system, often integrating with various data sources and applications across the Microsoft Power Platform.

Key Responsibilities:

• Design, build, and maintain data pipelines using Power Automate to extract data from diverse sources (databases, APIs, flat files, etc.), transform it as needed, and load it into target systems like data warehouses, data lakes, or business applications.
• Create automated workflows within Power Automate to streamline data processing tasks like data cleansing, validation, and data quality checks.
• Connect Power Automate to various Microsoft services like SharePoint, Dynamics 365, Azure, and Office 365 to facilitate seamless data flow between different systems.
• Implement data quality controls and data governance practices within Power Automate workflows to ensure data accuracy and consistency.
• Work with business analysts, data analysts, and other stakeholders to understand data requirements, translate them into Power Automate solutions, and deliver actionable insights.

Required Skills:

• Strong understanding of data warehousing concepts, data modeling, ETL processes, data quality best practices.
• Extensive experience designing and developing complex workflows using Power Automate, including connectors, triggers, actions, and data manipulation.
• Proficient in at least one programming language like Python, SQL, or C# for data manipulation and custom logic within Power Automate.
• Familiarity with Azure data services (Azure Data Factory, Azure Data Lake, Azure SQL Database) for large-scale data processing.
• Ability to analyze data using Power BI or other data visualization tools to identify trends and insights.