Sr. Data Engineer – AI/ML Platform (Healthcare Domain)

Senior Data Engineer – AI/ML Platform (GCP) 📍 Location: Remote (Dallas, TX Preferred) 💼 Employment Type: Contract We are seeking an experienced Senior Data Engineer to join a cutting-edge AI/ML initiative focused on building scalable, cloud-native data platforms that power advanced analytics, machine learning, and intelligent recommendation systems. Key Responsibilities • Design, build, and maintain large-scale data ingestion pipelines for structured and unstructured data sources. • Develop and optimize ETL/ELT workflows using modern cloud-native technologies. • Create and manage curated data marts and unified data views to support analytics and machine learning use cases. • Build and maintain feature engineering pipelines and datasets for AI/ML model training and inference. • Develop batch and real-time data processing solutions using streaming technologies. • Collaborate with Data Scientists, ML Engineers, and Application Development teams to support end-to-end AI initiatives. • Implement data quality frameworks, monitoring, alerting, and governance controls across the platform. • Optimize cloud data infrastructure for performance, scalability, reliability, and cost efficiency. • Design and support disaster recovery, backup, retention, and archival strategies for enterprise data platforms. • Ensure compliance with data security, privacy, and regulatory requirements in highly regulated environments. Required Qualifications • 7+ years of experience in Data Engineering or ML Data Engineering. • Strong hands-on experience with Google Cloud Platform (GCP). • Expertise in BigQuery, including data modeling, partitioning, clustering, and performance optimization. • Experience building streaming data pipelines using Apache Kafka. • Hands-on experience with Dataflow (Apache Beam) for batch and real-time processing. • Strong experience with Apache Spark/PySpark and large-scale data processing frameworks. • Proficiency in Python, Java, or Node.js for data engineering and automation. • Experience with Cloud Storage, Dataproc, Pub/Sub, and workflow orchestration tools such as Airflow/Composer. • Strong SQL skills and experience with modern data lake or lakehouse architectures. • Experience supporting machine learning workflows, feature engineering, and model training datasets. • Exposure to MLOps platforms, Feature Stores, and AI/ML pipeline orchestration tools is highly preferred. Preferred Qualifications • Experience working with healthcare, insurance, or other highly regulated industries. • Knowledge of data privacy, security, governance, and compliance frameworks. • Experience with disaster recovery planning, cross-region replication, and business continuity strategies. • Familiarity with data lifecycle management, archival, and retention policies. What We're Looking For • Strong problem-solving and analytical skills. • Ability to work independently in a fast-paced, collaborative environment. • Passion for building scalable data platforms that enable AI and machine learning innovation. 📩 If you have deep expertise in GCP, BigQuery, Kafka, Spark, and AI/ML data platforms, we'd love to connect.