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TechInsights

Semiconductor reverse engineering and market intelligence

Tableau Data Engineer & Modeler

Data Engineering +1Confirmed live in the last 24 hours
Full-timeDenver, CO, USA$86.3k - $91.3k

About the Job

Requirements

  • Have at least 4 years of experience in data engineering, analytics engineering, or business intelligence development, including at least 2 years building production Tableau data sources.
  • Have built and maintained at least 3 scheduled production Tableau Prep flows using complex joins, unions, pivots, and aggregations.
  • Have published at least 5 Tableau data sources used across multiple dashboards or teams, making clear decisions about relationships versus joins and extracts versus live connections.
  • Have at least 3 years of advanced SQL experience, ideally with PostgreSQL, including window functions, common table expressions, and materialized views; be able to demonstrate at least one query 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 obtaining stakeholder sign-off.
  • Have set up row-level security or user-based access controls in Tableau for at least one production data source.
  • Have at least 1 year of experience working with Salesforce data as a source, including objects, relationships, and history tables.
  • Be able to explain how the Model Context Protocol (MCP) and Tableau MCP server let AI agents read metadata and query data sources, and identify at least 3 model features that affect agent-answer accuracy.
  • Be able to provide at least 2 examples of technical documentation written for technical and non-technical readers, such as data dictionaries, lineage notes, or design decisions.
  • Submit latest citizenship and/or permanent-residency information for compliance with U.S. Export Control Laws and Regulations.

Responsibilities

  • Design certified, reusable published data sources as the single source of truth for core business entities, using validated business logic and the appropriate grain for each use case.
  • Standardize calculated fields, level-of-detail (LOD) expressions, and hierarchies at the data-source level to keep dashboards consistent.
  • Tune extracts and live connections for performance and refresh cost using aggregation, filtering, incremental refresh, and field pruning.
  • Prepare models for AI agents using the Tableau MCP server by creating clear field names, captions, descriptions, and metadata, and removing duplicate fields, unclear measures, and inconsistent date logic.
  • Test agent queries against the models, identify where answers are inaccurate, and correct the model rather than the prompt.
  • Help define Tableau Pulse metrics and the semantic layer used by people and AI agents.
  • Check each new or changed model and report against Finance-approved figures or the source system of record before release; explain and document discrepancies and obtain sign-off from the data owner before release.
  • Build automated data-quality checks between source systems and Tableau, and flag process failures to data owners.
  • Maintain lineage and documentation in Tableau Catalog or Data Management, and configure row-level security, user filters, and permissions according to the governance framework.
  • Build, schedule, and monitor Tableau Prep flows from Salesforce, PostgreSQL, and other sources; own run reliability, failure alerts, and recovery.
  • Refactor older flows and extracts to improve speed, maintainability, and refresh cost.
  • Work with Analysts, Sales, Finance, and Salesforce administrators to turn reporting needs into durable models, and train Tableau authors through documentation and code review.

Desired Qualifications

  • A current Tableau certification, such as Tableau Certified Data Analyst or Tableau Certified Architect.
  • Hands-on use of at least 2 of Tableau Pulse, Tableau Catalog or Data Management, VizQL Data Service, Tableau REST API, or Metadata API.
  • Experience testing LLM or AI-agent access to business intelligence data and measuring answer accuracy against a known source.
  • At least 1 year of Python experience for automation, API work, or Tableau Prep scripting steps.
  • Experience with AWS data services such as RDS, S3, or Lambda, and Git version control for data assets.
  • Experience with at least one other semantic layer or business intelligence tool, such as Power BI, Microsoft Fabric, or dbt.

About the Company

TechInsights

Semiconductor reverse engineering and market intelligence

TechInsights provides technical analysis and market intelligence for the semiconductor industry. It started by reverse-engineering electronics and turning findings into sellable reports, then expanded into an intelligence platform offering market forecasting, cost modeling, and supply-chain analysis. The company differentiates itself by combining deep engineering teardown insight with market analytics, aided by its history of merging with Chipworks and acquiring firms like VLSI Research, The Linley Group, Strategy Analytics, and IC Knowledge. Its goal is to be the go-to, one-stop intelligence platform for the semiconductor industry, helping customers make data-driven decisions and plan for the long term.

Company size
201-500
Company stage
Late Stage VC
Total funding
$10.6M
Headquarters
San Francisco, CA
Founded
1989

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