Job Description A client of Insight Global is looking to hire a ML Data Engineer to join their Software Engineering team. This person will be responsible for architecting, developing, and maintaining scalable data pipelines that support advanced analytics, machine learning, and real-time operational intelligence across enterprise systems. This person will be required to ingest, normalize, and interpret data from WMS platforms to support business-critical operations. You'll collaborate closely with software engineers, data scientists, and cross-functional teams to drive initiatives in data transformation, governance, and automation. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements • Minimum 5 years of experience in data engineering • Putting together, storing, and testing pipelines with ML Tools • Proficiency in Python, SQL, and modern data engineering practices. • Experience with Databricks, cloud-based architectures, and supporting AI/ML workflows. • Experience with real-time data gathering • Azure experience • Self-starter who can hit the ground running • Certifications in AI/ML or cloud technologies • Experience with Kafka