25 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You’ll split time between data work and web/app tasks. Morning might be checking dashboard refreshes, reviewing server logs (bandwidth, load, database performance), and fixing any broken data pipelines. Afternoons often mean building or updating Power BI reports, writing SQL for Amazon Redshift, or integrating data through AWS services like EC2 or S3.
You’ll also meet designers or developers to align visuals with the website, test cross-browser embedding of reports, update documentation (technical and functional), and log test plans or bug fixes. Expect intermittent support work: responding to user questions or restoring files from backups.
Start with Amazon Web Services (AWS) basics and Amazon Redshift, because Redshift is a common analytical database for Power BI. Learn how to connect Power BI to Redshift, run queries, and schedule refreshes.
Next learn EC2 (for running servers), S3 (for storage and backups), and general AWS console tasks like IAM (access control). Also get comfortable with AJAX and embedding techniques for web report integration.
U.S. employment and pay numbers are tracked by the Bureau of Labor Statistics (BLS). For a comparable occupational group in 2025, BLS reports about 70,190 employed with a median annual wage of $92,650. The lowest tenth earned $48,100 and the top tenth earned $162,290 per year.
Pay varies by region, experience, and employer. Roles that add AWS, Redshift, or full-stack web responsibilities usually pay higher. Use BLS as a baseline and check local job listings for current rates.
Begin with Power BI Desktop: build reports from Excel and CSV files, then practice connecting to databases like Redshift. Follow Microsoft’s free learning paths and do small projects you can show.
Parallel-track AWS fundamentals: take an introductory AWS course covering EC2, S3, and IAM. Practice deploying a simple web page that embeds a Power BI report (use AJAX for interactions). Keep a short portfolio and document your architecture diagrams, test plans, and backup procedures.
A Power BI developer focuses on analytics: designing reports, dashboards, data modeling, and connecting BI tools to databases like Redshift. You also handle embedding reports into websites and ensuring responsiveness and cross-browser compatibility.
A web developer focuses more on site architecture, front-end code, and server setup (HTTP servers, directory trees). A data engineer builds and maintains the data pipelines and databases. In many teams these roles overlap: you may write SQL, configure EC2 instances, and collaborate with designers and engineers.
AI can speed up tasks: generate DAX measures, suggest SQL queries for Redshift, write PowerShell to back up files, or draft documentation and test plans. Use it to prototype code or write unit test ideas, but always review and test outputs thoroughly.
Risks: AI may invent incorrect queries or security-sensitive commands. Never run generated code against production databases or servers without validating it. Keep secrets out of prompts and follow your company’s data and security policies.
Be solid at data modeling and DAX in Power BI, and at writing efficient SQL for systems like Amazon Redshift. These drive report performance and correctness.
Also learn how to deploy and monitor services on AWS (EC2, S3), understand embedding techniques (AJAX, responsive design), and document test plans, server metrics, and functional details. Troubleshooting web issues and setting up backups are everyday responsibilities.