20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You spend part of the day building and testing dashboards in Tableau and the rest connecting data from sources like Amazon Redshift or DynamoDB. Expect to write queries, tweak visuals, and run performance checks after deployment.
You also attend stand-ups with developers, review code or workbook changes, document what you built, and help users who report issues or need training on new dashboards.
Common systems are Amazon Redshift for data warehousing, DynamoDB for key-value storage, and data prep tools like Alteryx. Your Tableau workbooks will connect to these systems for queries and extracts.
On cloud infrastructure you may touch AWS services such as EC2 for compute or CloudFormation for infrastructure scripts, and you might embed AJAX-driven visuals in web portals.
Use AI to generate SQL snippets, suggest chart types, or clean data in Alteryx, but always review outputs. Verify any AI-created queries against the source data and your performance standards before publishing.
Keep security in mind: do not paste sensitive credentials into AI tools, follow company data-protection rules, and log changes so you can trace what automation changed in a dashboard or dataset.
According to the U.S. Bureau of Labor Statistics (BLS, 2025), there are 1,687,890 employed in related computer and information roles. Median pay is $135,980 per year; the lowest tenth is $82,460 and the top tenth is $214,670.
Your salary depends on experience, industry, and city. Specialist skills like Redshift, AWS, Alteryx, and strong dashboard UX often push candidates toward the higher ranges.
Begin with Tableau Desktop training: learn connecting to data, creating calculated fields, and publishing to Tableau Server or Online. Pair that with SQL practice aimed at Amazon Redshift (Postgres-flavored SQL).
Add Alteryx or another ETL tool to learn data cleaning, then basic AWS concepts—how EC2 instances run compute and how CloudFormation automates infra. Build a few end-to-end projects and document them.
A Tableau Developer focuses on designing and deploying Tableau dashboards and the visual UX, plus connecting and optimizing queries to data platforms like Redshift. They often handle deployment and user training.
A BI Engineer builds data pipelines and may work more with ETL systems and database schema design. A Data Analyst interprets data and produces reports but might not manage Tableau Server, CloudFormation scripts, or production deployments.
Show you can store, retrieve, and manipulate data: demonstrate SQL queries on Redshift and ability to prepare data in Alteryx. Include examples of debugging slow dashboards and improving performance.
Also show version control or documentation for deployments (CloudFormation or change logs), UI/UX sense in dashboard design, and how you supported or trained users after release.