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Position: Data and Automation Engineer Job Description: Position Summary The Data & Automation Engineer is responsible for designing, developing, and maintaining scalable data solutions that integrate information from multiple enterprise platforms and transform it into actionable business insights. This role focuses on data engineering, data integration, automation, analytics enablement, and AI-driven solutions. The ideal candidate should be comfortable working across the full data lifecycle, from data ingestion and transformation to reporting, automation, and AI integration. This is primarily a Data Engineering role with Power BI reporting responsibilities, rather than a reporting-only or dashboard-focused position. Key Responsibilities Data Integration & Engineering Design, develop, and maintain ETL/ELT data pipelines. Integrate data from multiple enterprise systems including: Salesforce SharePoint Supplier systems Support platforms (tickets, Q&A, case management systems) External APIs Develop scalable and maintainable data models. Ensure data quality, consistency, lineage, and traceability across systems. Work with structured and unstructured data sources. Business Intelligence & Analytics Develop and maintain Power BI semantic models, dashboards, and reports. Create DAX measures and business logic to support operational reporting. Translate business requirements into meaningful KPIs and actionable insights. Automate report generation and data refresh processes. Automation & AI Develop automation solutions using Python and workflow orchestration tools. Integrate AI services into business processes and analytics workflows. Develop solutions such as: Automated insights Ticket classification Trend analysis Knowledge retrieval AI assistants and agent-based workflows Evaluate and implement modern AI technologies where appropriate. Collaboration Work closely with support, integration, engineering, and business teams. Help define data strategies and identify automation opportunities. Promote best practices in data governance and solution design. Required Technical Skills (Must Have) Data Engineering Strong experience building ETL/ELT pipelines. Strong experience integrating data from multiple systems. Experience consuming and integrating REST APIs. Experience working with structured and unstructured data. Advanced SQL skills. Power BI Data Modeling DAX Dashboard and report development Performance optimization Programming Strong Python skills for: Data processing Automation API integrations Analytics workflows General Ability to independently design and implement technical solutions. Strong troubleshooting and analytical skills. Experience working in enterprise environments. Preferred Skills Candidates with experience in one or more of the following areas are highly desirable: AI and Large Language Models (LLMs) Copilot Studio OpenAI, Azure OpenAI, Anthropic, Gemini, or similar AI platforms RAG (Retrieval Augmented Generation) solutions Agent-based automation Power Automate n8n Machine Learning applications Cloud-based data platforms Equivalent technologies are welcome. Experience integrating business solutions is more important than experience with a specific vendor or cloud platform. What We Are Looking For The ideal candidate has experience: Building ETL/ELT pipelines Integrating data from APIs and multiple enterprise systems Using Python in production environments Creating Power BI semantic models and DAX measures Designing solutions end-to-end Automating business processes Applying AI technologies to real business scenarios Please attach CV in English. #LI-MS1 Location: HU-Budapest, Hungary (Váci út) Time Type: Full time Job Category: Engineering and Technology
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.