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AI Engineer

Jobot

Addison, TX

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JOB DETAILS
SALARY
$120,000–$160,000 Per Year
SKILLS
Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Call Center Operations, Continuous Deployment/Delivery, Continuous Integration, Cost Control, DOMO, Data Analysis, Data Cleaning, Data Management, Data Modeling, Data Quality, Database Design, Database Technology, Documentation, Electricity, Finance, HVAC, Incident Response, Intuit Quickbooks, Leadership, Legal, MCP - Microsoft Certified Professional, Marketing, Metrics, NoSQL, On Site Support, Paycom, Plumbing, Production Systems, Project Engineering, Python Programming/Scripting Language, Query Optimization, REST (Representational State Transfer), Risk, SQL (Structured Query Language), Sales Pipeline, Scaffolding, Scripting (Scripting Languages), Search Agent, Secure/SSH File Transfer Protocol (SFTP), Service Level Agreement (SLA), Snowflake Schema, Standard Operating Procedures (SOP), Star Schema, Vendor/Supplier Evaluation, Warehousing
LOCATION
Addison, TX
POSTED
2 days ago
AI Engineer - Hybrid

This Jobot Job is hosted by: Melanie Courtney
Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume.
Salary: $120,000 - $160,000 per year

A bit about us:

Our client is a collection of industry-leading residential and commercial HVAC, electrical, and plumbing companies. Our mission is to provide exceptional residential and commercial services by upholding the legacies of our brand partners, empowering their growth, elevating performance, and enhancing the quality of life in the communities we serve.

Why join us?

Growing company
Top benefits
Great culture

Job Details

1. Data Engineering & Snowflake Platform | Primary Focus
  • Design and own the three-layer Snowflake architecture: RAW → STAGING → MART
  • Build and maintain domain MARTs (operations, call center, finance, workforce, marketing) using dbt — grain, ownership, SLA, and data contracts defined per MART
  • Own Snowflake RBAC — Domo read-only on MART, AI scoped to mart.ai_features, row-level policies and masking applied where needed
  • Build and maintain Semantic Views as the authoritative metric layer (booked rate, avg ticket, revenue per tech per day) — single source of truth for all tools
  • Monitor pipeline health, warehouse costs, and query performance; optimize proactively

2. Data Ingestion & ETL/ELT | Core Ownership
  • Own ingestion end-to-end — Fivetran is the primary tool; configure and manage connectors for ServiceTitan, QuickBooks/Sage Intacct, Paycom, CCaaS, and marketing platforms
  • Handle sources Fivetran does not cover with lightweight Python scripts (SFTP, REST APIs, email-delivered files); bias toward replacing custom scripts with managed connectors over time
  • Own the dbt project as an engineering artifact — structure, CI/CD, dev/prod environments, packages, documentation
  • Manage schema drift — catch upstream source changes before they break downstream MARTs; configure Fivetran schema change policies and dbt source assertions
  • Define and maintain pipeline SLAs and alerting — failures surface before business users notice
  • Own data lineage — every MART table traceable to source via dbt lineage graph
  • Manage Fivetran MAR costs — optimize sync frequency without sacrificing freshness

3. AI Engineering | Built on the Data Foundation
  • Implement Cortex Analyst + Semantic Views for NL-to-SQL querying of MARTs — no SQL required for GMs and ops users
  • Build enterprise knowledge search via Cortex Search — SOPs, runbooks, and operational docs indexed within the Snowflake perimeter
  • Deploy Cortex Agents orchestrating across Cortex Search and Cortex Analyst for multi-step business questions
  • Connect external systems (ServiceTitan, M365) via Snowflake MCP Server; use N8N or LangChain for workflows outside Snowflake
  • Build AI feature pipelines in mart.ai_features under the same governance standards as all other MARTs

4. Governance & Enablement
  • Define AI governance framework: acceptable use, risk tiers, PII handling, vendor evaluation
  • Ensure AI pipelines inherit existing Snowflake RBAC and masking — no parallel governance layer
  • Train end users on CoWork and Cortex Analyst; build internal tools for ops, finance, and service teams

First 90 Days
  • Audit Domo pipelines and produce a source inventory — ingestion method, refresh schedule, and downstream consumers for every source
  • Stand up Snowflake three-layer architecture, RBAC, and dbt project scaffold with dev/prod environments
  • Configure first Fivetran connectors (ServiceTitan first); ship mart.operations with dbt tests passing and Domo read-only connected
  • Deliver AI governance framework and acceptable use policy
  • Present 12-month roadmap to leadership — ingestion milestones gating MART build gating AI capabilities

Our Tech Stack

Data Warehouse (required) Snowflake + Cortex AI (Cortex Agents, Cortex Search, Cortex Analyst, Semantic Views)
Data Ingestion (required) Fivetran (strongly preferred); Airbyte or equivalent considered; Domo Writeback (transitional); Python for uncovered sources
Data Transformation (required) dbt — models, tests, sources, snapshots, incremental, CI/CD
BI / Visualization Domo (read-only MART layer)
AI / LLM Claude (Anthropic) — direct API and via Cortex
Field Service Platform ServiceTitan
Productivity Stack Microsoft 365, SharePoint, Teams


What We're Looking For
Required — Data Engineering
  • 4+ years owning production data pipelines as a data engineer or analytics engineer
  • Expert SQL; strong data modeling — star schema, SCD Types 1/2, incremental load patterns
  • Hands-on dbt in production — models, tests, sources, snapshots, macros, CI/CD, project ownership
  • Managed connector experience — Fivetran strongly preferred; Airbyte, Stitch, or equivalent considered if connector setup, schema mapping, schema change policies, and MAR/MTU cost management are demonstrated
  • Direct Snowflake experience — schema design, warehouse management, RBAC, query optimization, task scheduling; SnowPro Core preferred
  • Domain MART design — grain, SLA, ownership, and data contracts a small team can maintain
  • Pipeline monitoring and observability — SLA definition, drift alerting, and incident response before business users are impacted; experience with Elementary, Monte Carlo, or dbt’s built-in freshness and source monitors preferred
  • Python for custom ingestion — SFTP, REST APIs, email-delivered files
  • Data quality as default — dbt tests, freshness monitors, and schema assertions in every pipeline

Required — AI Foundation
  • Genuine drive to build AI capabilities; understands clean data is the prerequisite to reliable AI
  • LLM API experience (Anthropic, OpenAI, or equivalent) — prompt engineering, structured outputs, basic agent patterns
  • Familiarity with RAG and vector search; able to implement Cortex Search without prior vector DB experience
  • Python for pipeline scripting and API integration

Preferred
  • Snowflake Cortex AI hands-on — Cortex Analyst, Cortex Search, Cortex Agents, or Semantic Views
  • Multi-location or multi-brand data environment
  • ServiceTitan or field service platform experience
  • AI governance framework experience (NIST AI RMF or equivalent)


Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions.

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About the Company

J

Jobot

Jobot is on a mission to connect good people with good jobs. By combining AI-powered technology with the expertise of Jobot Pros, our experienced recruiters, we help you find career opportunities that align with your goals and values.

Founded in 2018 and employee-owned since 2024, Jobot is committed to fostering a culture of kindness, respect, innovation, and connection.  As an industry leader, we’ve been recognized as a top workplace by Forbes, Fortune, USA Today, and Staffing Industry Analysts (SIA).

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COMPANY SIZE
100 to 499 employees
INDUSTRY
Staffing/Employment Agencies
FOUNDED
2018
WEBSITE
http://www.jobot.com