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26-1136: AI Engineer 3 - Herndon, VA
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Added 9 mins ago
Decision scientist - Market Planning and Business Systems
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TechInsights

Tableau Data Engineer & Modeler

Denver, CO, United States

Expected salary range: $86,275 - $91,350 USD

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Job details

Pay: Expected salary range: $86,275 - $91,350 USD
Apply by: Feb 4, 2027
Posting language: English
Posted: Nov 6, 2026

Original job description

OUR STORY

TechInsights is the information Platform for the semiconductor industry.

Regarded as the most trusted source of actionable, in-depth intelligence related to semiconductor innovation and surrounding markets, TechInsights’ content informs decision makers and professionals whose success depends on accurate knowledge of the semiconductor industry - past, present, or future.

Over 650 companies and 150,000 users access the TechInsights Platform, the world’s largest vertically integrated collection of unmatched reverse engineering, teardown, and market intelligence in the semiconductor industry. This collection includes detailed circuit analysis, imagery, semiconductor process flows, device teardowns, illustrations, costing and pricing information, forecasts, market analysis, and expert commentary. TechInsights’ customers include the most successful technology companies who rely on TechInsights’ analysis to make informed business, design, and product decisions faster and with greater confidence. For more information, visit www.techinsights.com.

WHY WORK WITH US

Company-sponsored training and development opportunities
Comprehensive benefits package (health, dental, vision, wellness, RRSP/401K Matching, annual fitness reimbursement)
Flexible vacation policy
Trusted device reimbursement program
Community involvement opportunities through charitable alliances: https://www.techinsights.com/community-involvement
Wellness resources and support
Inclusive environment that prioritizes diversity, equity, and accessibility
High-growth company driven by high performance
Expected salary range: $86,275 - $91,350 USD

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

As part of the recruitment process for this position, you will be required to submit your latest citizenship and/or permanent residency information. This information will be used to comply with U.S. Export Control Laws and Regulations.

WORKING ARRANGEMENT

This role is on-site at our Denver office. Technology knows no bounds, and neither does TechInsights. Bringing together talented humans from different perspectives, backgrounds and abilities is something we take seriously. We’re committed to building an inclusive environment that welcomes you to be your authentic self and allows us to push past the boundaries together.

TechInsights is committed to meeting the needs of people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.

AI technology may be used to assist in the screening and assessment of applications for this position. Our recruiters are involved at every stage, and all hiring decisions are made by People and hiring teams.

As part of any recruitment process, TechInsights collects and processes personal data relating to job applicants. We are committed to being transparent about how we collect and use that data and to meeting our data protection obligations. Our Privacy policy can be referenced here: https://www.techinsights.com/privacy-policy

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More about this job

Skills

Tableau
Data analysis
Leadership
Data models
Statistical quality control
Documentation
Data management
Salesforce
PostgreSQL
Sales
Reporting
Data engineering
SQL
Python
AWS
Git
Microsoft Power BI
dbt
Recruitment

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