AI Product Engineer

Shermco Industries

. Own and build end-to-end data pipelines within Microsoft Fabric .

Posted 11/5/2026full-timeIrving • Texas • United StatesMid-LevelSenior💰 $150,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building end-to-end data pipelines using Microsoft Fabric and Azure tools, with strong capabilities in SQL, Python, and Spark for data transformation and modeling. Proficient in applying AI/ML techniques for data processing and analytics, while collaborating effectively within multi-disciplinary teams.

Highest-signal resume keywords

End-To-End Data Pipeline DevelopmentSQL Data TransformationPython ProgrammingMicrosoft Fabric ExperienceAI/ML Techniques Application

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data IngestionData TransformationData ModelingMachine LearningData ValidationData IntegrationData CleaningPredictive ModelingRegression AnalysisNatural Language Processing

Soft Skills

CollaborationAutonomyProblem-SolvingCommunicationAgile Methodologies

Tools & Technologies

Microsoft FabricAzure Data FactoryAzure SynapseDatabricksJiraGitCI/CD PracticesPower BI

Industry Keywords

Data EngineeringAnalytics EngineeringERP SystemsSaaS SystemsFile-Based SourcesAI/ML CapabilitiesBusiness Intelligence

Tech Stack

Tools & technologies

AzureERPPythonSparkSQL

About the role

Key responsibilities & impact

Own and build end-to-end data pipelines within Microsoft Fabric
Ingest and transform data from ERP systems, CRM/SaaS systems, and file-based sources
Deliver reliable, validated, well-structured datasets for analytics and operational needs
Build analytics-ready datasets inside Fabric Lakehouse/Warehouse architecture
Use SQL, Python, and Spark to normalize, join, enrich, and clean data
Design simple, transparent, and scalable data modeling patterns
Prepare training datasets, run models, evaluate outcomes, and integrate results into pipelines and analytics products
Apply AI/ML techniques to process automation, forecasting, predictive modeling, classification, and unstructured-data extraction and enrichment
Use Fabric, Azure Foundry, and other AI/ML capabilities in practical applications
Implement testing, validation, error handling, monitoring, Git, and CI/CD practices
Collaborate with BI, database engineering, and business analysis teammates
Participate in requirements definition, output validation, troubleshooting, backlog management, sprint planning, and progress tracking using Jira
Break complex initiatives into manageable increments
Stay current with Microsoft Fabric and Azure AI advancements and propose improvements

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field or equivalent professional experience
3–7+ years of hands-on experience in data engineering, analytics engineering, or applied machine learning
Deep experience with SQL and Python for data ingestion, transformation, and integration
Experience with Microsoft Fabric or Azure data ecosystem tools (Data Factory, Synapse, ADLS, Databricks)
Proven ability to extract, transform, and model data from ERPs, SaaS systems, APIs, and file-based sources
Familiarity with Spark for larger-scale transformations
Experience applying AI/ML techniques in real-world scenarios (regression, forecasting, classification, NLP, enrichment, etc.)
Ability to work autonomously and collaborate within a small, multi-disciplinary team
Experience working in iterative frameworks (Agile, Scrum, or similar) using Jira or equivalent tools
Relevant certifications and advanced degrees are a plus but not required
Helpful, not required: experience with Business Central or similar ERP systems; exposure to Power BI semantic modeling concepts; experience deploying or operationalizing ML models; familiarity with Azure AI, Copilot, or LLM-based enrichment