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SI

Shermco Industries, Inc.

via Icims

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Data Engineer - AI Focused

Anywhere
full-time
Posted 11/21/2025
Direct Apply
Key Skills:
SQL
Python
Spark
Data Engineering
AI/ML Techniques
Microsoft Fabric
Azure Data Ecosystem
Data Pipeline Development
Applied Machine Learning

Compensation

Salary Range

$115K - 140K a year

Responsibilities

Build and maintain end-to-end data pipelines, apply AI/ML techniques, collaborate across teams, and continuously improve data and AI capabilities within Microsoft Fabric and Azure environments.

Requirements

3-7+ years in data engineering or applied machine learning, proficiency in SQL, Python, Spark, experience with Microsoft Fabric/Azure tools, and applied AI/ML experience.

Full Description

Overview Job Title: Senior Data Engineer Location: Remote (Must be located in Central or Eastern time zone) Department: Information Technology Reports To: Data & Analytics Director Job Overview We are growing our data capabilities and are looking for a Senior Data Engineer to help us build the next stage of our analytics and AI journey. You’ll join a small, collaborative team that already has strengths in database operations, business intelligence, and stakeholder engagement. What we need now is someone who can bring in deeper data engineering expertise and applied AI/ML experience—and help guide us into what’s possible. This is a hands-on role where you will work across the full data lifecycle—ingesting, transforming, modeling, enriching, and applying advanced analytics. You’ll help us navigate and adopt the rapidly evolving Microsoft Fabric and Azure AI ecosystem. We are early in our AI/ML journey, and you will play a key role in shaping and growing these capabilities alongside the rest of the team. If you’re excited to build practical, meaningful data solutions and explore real AI/ML opportunities in a collaborative environment, this is the place for you. Responsibilities Key Responsibilities Data Engineering & Integration Own and build end-to-end data pipelines within Microsoft Fabric. Ingest and transform data from: ERP systems (e.g., Business Central using SQL, APIs, or OData) CRM/SaaS systems (Salesforce, Dayforce, etc.) File-based sources (CSV, JSON, Excel, cloud storage, SFTP, etc.) Deliver reliable, validated, well-structured datasets for analytics and operational needs. Keep pipelines lean, maintainable, and aligned with team capacity. Data Modeling & Transformation Build clear, analytics-ready datasets inside Fabric Lakehouse/Warehouse architecture. Utilize SQL, Python, and Spark to normalize, join, enrich, and clean data. Design modeling patterns that fit our team and business—simple, transparent, and scalable. Applied AI/ML Bring real-world experience applying AI/ML techniques and understanding the landscape of available approaches. Prepare training datasets, run models, evaluate outcomes, and integrate results back into pipelines and analytics products. Apply ML and AI techniques to use cases such as: Process automation assisted by generative AI Forecasting and predictive modeling Classification or enrichment of structured/semi-structured data Extraction and enrichment of unstructured data (text, documents, etc.) Use Fabric, Azure Foundry and other AI/ML capabilities in practical, value-driven ways. Help the team explore new AI/ML opportunities as you learn our business and data, your ideas will shape our direction. Quality, Reliability & Maintainability Implement testing, validation, error handling, and monitoring across pipelines and models. Use Git and CI/CD practices appropriate to our environment. Keep solutions simple, maintainable, and well-documented. Cross-Team Collaboration & Iterative Workstyle Work with teammates focused on BI, database engineering, and business analysis to deliver complete data solutions. Participate in defining requirements, validating outputs and troubleshooting issues. Work in a light Agile environment, using tools like Jira for backlog management, sprint planning, and tracking work progress. Help break down complex initiatives into manageable increments that deliver value continually. Continuous Learning & Evolution Stay current with Microsoft Fabric and Azure AI advancements. Proactively propose improvements, new approaches, and opportunities. Grow your expertise and ownership of our AI/ML capabilities over time. Qualifications Qualifications and Skills Education and Experience: 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. Relevant certifications (Microsoft, Azure, Fabric, AI/ML) or advanced degrees are a plus but not required. Skills and Technical Experience: 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. Additional Experience (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. EQUAL OPPORTUNITY EMPLOYER | DRUG-FREE WORKPLACE Shermco is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. Shermco is a drug-free workplace. NO AGENCIES PLEASE Pay Range USD $115,000.00 - USD $140,000.00 /Yr.

This job posting was last updated on 11/24/2025

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