Data Engineer

Title: Data Engineer – AI/ML Pipelines Location: Seffner, FL Type: 6-Month Contract-to-Hire (Hybrid: 3 days onsite, 2 days remote) Pay: $90,000 – $140,000 annually (based on experience) Summary: We’re looking for an experienced Data Engineer with a strong focus on AI and machine learning pipelines. This role involves building scalable, production-ready data workflows that power ML models and real-time analytics. The ideal candidate will have a solid background in data ingestion, transformation, orchestration, and governance—particularly involving Warehouse Management Systems (WMS), ERP systems, and operational telemetry. If you have a passion for enabling intelligent systems through robust data engineering, this is a high-impact opportunity. Requirements: • 5+ years of experience in data engineering, with at least 2 years supporting AI/ML use cases • Strong skills in Python, SQL, and tools like dbt, Spark, or Delta Lake • Hands-on experience designing and managing ML-focused data pipelines • Proficient in cloud data ecosystems, especially Azure and Databricks • Familiarity with tools like MLflow, TFX, or equivalent ML pipeline frameworks • Experience working with WMS or logistics/operational data • Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (Master’s preferred) • Relevant certifications such as Azure AI Engineering, Databricks ML Associate, or Google Professional Data Engineer are a plus Responsibilities: • Build and maintain scalable data pipelines tailored to machine learning workflows • Collaborate with data scientists to deliver high-quality, ML-ready datasets • Design and automate workflows using tools like Azure Data Factory, Airflow, or Databricks Workflows • Ingest and transform structured/unstructured data from WMS, ERP, and telemetry systems • Implement feature stores, model input validation, and model monitoring solutions • Ensure high data quality through anomaly detection, validation checks, and reconciliation • Participate in cross-functional collaboration with engineering, data science, and operations teams • Document pipeline logic and mentor junior engineers in best practices for ML data engineering • Support real-time and batch data needs in a dynamic, innovation-driven environment This hybrid position typically requires 3 days onsite each week in Seffner, FL, with flexibility depending on candidate availability.