Hiring: Principal Data Engineer Company: SS&C Technologies Location: Waltham, MA Job Posted Time: 2026-09-16 22:20:22 Employment Type: Hybrid Target Skills & Keywords : AWS, Airflow, Azure, C, CI/CD, Data Lake, Django, Docker, EC2, FastAPI, Flask, GCP, Grafana, Java, Jenkins, Keras, Kubeflow, Kubernetes, Linux, MLOps, Machine Learning, Microservices, Milvus, MongoDB, Pinecone, PostgreSQL, PyTorch, Python, REST, RESTful, Root Cause Analysis, S3, Snowflake, Spark, Splunk, Terraform, scikit-learn About the job Experience: •Strong Python programming skills with hands-on experience using frameworks such as Flask, Django, FastAPI, or Celery. •Solid experience with ML SDLC, microservices architecture, and productionizing Python or Java applications. •Applied hands-on capability in AWS (EC2, S3, Data Lake), Kubernetes, and CI/CD tooling including Jenkins, Terraform, Splunk, and Grafana. •Operational familiarity with ML frameworks (PyTorch, Keras, scikit-learn) and experience building end-to-end data and ML pipelines. •Proven experience with RESTful API development, containerized deployments (Docker/Kubernetes), and delivering scalable ML models in production. Required Skills: •SS&C combines proprietary technology with deep industry expertise to support complex financial and health care operations. Our teams design, implement, and operate solutions that help clients manage data, automate processes, and scale their businesses with confidence. •Work with industry experts, modern platforms, and evolving technologies, gaining exposure to real-world operational challenges and large-scale enterprise environments. •How You Will Make An Impact •Build scalable, self-service ML model deployment pipelines that enable teams to move from experimentation to production with speed and reliability. •Design cloud-native ML workflows aligned with organizational strategy and modern MLOps principles. •Develop tooling for model development, deployment, monitoring, and reporting across the full ML lifecycle. •Create and maintain RESTful APIs for model lifecycle management, ensuring scalability, security, and reliability. •Partner with Data Scientists and Engineers to operationalize ML solutions and bridge the gap between research and production. Qualifications: •8+ years of relevant experience in data engineering, ML engineering, or a related field, with a Bachelor’s degree in Computer Science or a quantitative discipline. •Master’s degree in Computer Science, Data Science, or a related quantitative field. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!