Data Engineer - AI Focused

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer – AI Focused in the United States. This role is designed for an experienced data engineering professional with a strong focus on AI and applied machine learning. You will work across the full data lifecycle, from ingestion and transformation to modeling and analytics, helping the organization scale its data capabilities and adopt emerging AI technologies. The position requires collaboration with a small, skilled team and offers the opportunity to shape data and AI/ML strategy, implement practical, high-value solutions, and explore innovative ways to leverage data. You will work with a variety of systems including ERP, CRM, SaaS, and unstructured data sources, delivering reliable datasets and AI-powered insights that support operational and analytical decision-making. This is a hands-on, impactful role in a dynamic, learning-focused environment. Accountabilities: · Design, build, and maintain end-to-end data pipelines within Microsoft Fabric and Azure ecosystems. · Ingest and transform data from ERP systems (e.g., Business Central), CRM/SaaS platforms (Salesforce, Dayforce), and file-based sources (CSV, JSON, Excel, cloud storage, SFTP). · Develop analytics-ready datasets using SQL, Python, and Spark; normalize, join, enrich, and clean data. · Apply AI/ML techniques to real-world use cases such as forecasting, predictive modeling, process automation, and text or document enrichment. · Ensure quality, reliability, and maintainability of data solutions through testing, validation, error handling, monitoring, and CI/CD practices. · Collaborate with cross-functional teams including BI, analytics, and business analysis to deliver complete data solutions. · Participate in Agile workflows, breaking down complex initiatives into manageable increments while continuously proposing improvements. · Bachelor’s degree in Computer Science, Data Science, Software Engineering, or equivalent experience. · 3–7+ years of hands-on experience in data engineering, analytics engineering, or applied AI/ML. · Proficiency in 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 ERP, SaaS, APIs, and file-based sources. · Familiarity with Spark and applied AI/ML techniques (regression, forecasting, classification, NLP, enrichment). · Strong collaboration skills and experience working in iterative frameworks (Agile, Scrum, Jira). · Optional but valuable: certifications in Microsoft/Azure, experience with Business Central, Power BI modeling, deploying ML models, Azure AI, or LLM-based enrichment. · Competitive annual salary: USD $115,000 – $140,000. · Comprehensive health and wellness benefits. · Flexible, remote-first work environment within Central or Eastern time zones. · Opportunities for professional development, certifications, and continuous learning. · Collaborative, learning-focused team environment. · Exposure to cutting-edge AI/ML tools and Microsoft Fabric/Azure data ecosystem. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience and achievements. It compares your profile to the job’s core requirements and past success factors to determine your match score. Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1 Apply tot his job