Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Power Automate Data Engineer

Vallum Associates
Leeds
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Data Engineer

Data Engineer (Python & Databricks)

Graduate Data Analyst

Operations Data Analyst - Global Logistics

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.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.