THE OPPORTUNITY:TechInsights' Data & Analytics team turns corporate data into clear insights that guide leadership's decisions on operations and new business initiatives. As our Tableau Data Engineer & Modeler, you'll own the pipelines and data models behind our Tableau Cloud environment. You'll build and maintain Tableau Prep flows and design published data sources that are fast, trusted and well governed. You'll also shape those models so they work as well for AI agents using the Tableau MCP server as they do for people building dashboards. This is a hands-on role close to our core source systems (Salesforce, PostgreSQL on AWS and NetSuite). You'll have real ownership of our Tableau data structure and work directly with the people who use the data.
WHAT YOU'LL DO - Design certified, reusable published data sources that become the single source of truth for core business entities, using validated business logic and the right grain for each use case.
- Standardize calculated fields, LOD expressions and hierarchies at the data-source level so dashboards stay consistent.
- Tune extracts and live connections for performance and refresh cost through aggregation, filtering, incremental refresh and field pruning.
- Prepare models for AI agents using the Tableau MCP server. This means writing clear field names, captions, descriptions and metadata, and removing duplicate fields, unclear measures and inconsistent date logic.
- Test agent queries against our models, find where answers go wrong, and fix the model rather than the prompt.
- Help define Tableau Pulse metrics and the semantic layer that both people and agents rely on.
- Check every new or changed model and report against Finance-approved figures or the source system of record before release. Nothing goes live until differences are explained, documented and signed off by the data owner.
- Build automated data quality checks between source systems and Tableau, and flag process failures to data owners.
- Maintain lineage and documentation in Tableau Catalog / Data Management, and set up row-level security, user filters and permissions that follow our governance framework.
- Build, schedule and monitor Tableau Prep flows from Salesforce, PostgreSQL and other sources. You'll own run reliability, failure alerts and recovery.
- Refactor older flows and extracts so they're faster, easier to maintain and cheaper to refresh.
- Work with Analysts, Sales, Finance and Salesforce admins to turn reporting needs into durable models, and train Tableau authors through documentation and code review.
WHAT YOU'LL BRING - 4+ years in data engineering, analytics engineering or BI development, including 2+ years building production Tableau data sources
- Have built and maintained at least 3 production Tableau Prep flows that run on a schedule and use complex joins, unions, pivots and aggregations
- Have published at least 5 Tableau data sources used across multiple dashboards or teams, with clear decisions on relationships vs. joins and extracts vs. live connections
- 3+ years writing advanced SQL, ideally PostgreSQL, including window functions, CTEs and materialized views. You can show at least one query you improved by reading its query plan.
- Have designed at least one dimensional model (star schema) end to end, covering grain, slowly changing dimensions, conformed dimensions and many-to-many relationships
- Have reconciled data models or reports to financial or system-of-record figures at least twice, documenting differences and getting stakeholder sign-off
- Have set up row-level security or user-based access controls in Tableau for at least one production data source
- 1+ year working with Salesforce data as a source, including objects, relationships and history tables
- Can explain how the Model Context Protocol (MCP) and the Tableau MCP server let AI agents read metadata and query data sources, and name at least 3 model features that make agent answers more or less accurate
- Can share 2+ examples of technical documentation you wrote, such as data dictionaries, lineage notes or design decisions, for both technical and non-technical readers
Preferred
- A current Tableau certification, such as Tableau Certified Data Analyst or Tableau Certified Architect
- Hands-on use of at least 2 of these: Tableau Pulse, Tableau Catalog / Data Management, VizQL Data Service, Tableau REST API or Metadata API
- Have tested LLM or AI agent access to BI data and measured how accurate the answers were against a known source
- 1+ year using Python for automation, API work or Tableau Prep scripting steps
- Experience with AWS data services (RDS, S3, Lambda) and Git version control for data assets
- Experience with at least one other semantic layer or BI tool, such as Power BI / Microsoft Fabric or dbt
WORKING ARRANGEMENTThis role is on-site at our Denver office.
