Principal Data Engineer

Principal Data Engineer 

Locations: Waltham, MA - Hybrid

About the Role 

We are seeking a highly skilled and hands-on Principal Data Engineer to lead the design, and development of scalable real-time data platforms and distributed data processing systems. This role requires deep expertise in Java-based backend engineering, microservices architecture, event-driven systems, Apache Kafka, Apache Flink, cloud-native platforms, and AWS technologies. 

The ideal candidate will have extensive experience building enterprise-scale streaming platforms, developing resilient microservices, optimizing large-scale data pipelines, and driving engineering best practices. This role will collaborate closely with Product, Architecture, Application Development, Analytics, SRE, and DevOps teams to deliver highly scalable, reliable, and high-performance data solutions. 

Why Join SS&C  

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.  

You will 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   

• Lead the design, and development of scalable real-time data platforms and event-driven streaming solutions using Apache Kafka, Apache Flink, Java, Spring Boot, and AWS cloud-native technologies. 

• Design and implement high-performance batch and streaming data pipelines with advanced stream-processing capabilities including stateful processing, windowing, event-time processing, checkpointing, fault tolerance, and exactly once semantics. 

• Develop scalable microservices, REST APIs, reusable data frameworks, and enterprise data processing components. 

• Drive platform modernization, technical design reviews, engineering standards, and adoption of innovative technologies to improve scalability, reliability, performance, and operational efficiency. 

• Design and maintain cloud-native infrastructure, CI/CD pipelines, deployment automation, and containerized applications using Kubernetes, Docker, Terraform/CloudFormation, ECS/EKS, and AWS services including S3, MSK, Redshift, Aurora, RDS, Lambda, Glue, and CloudWatch. 

• Design optimized relational and analytical data models using Oracle, PostgreSQL, Redshift, and Aurora, including performance tuning, indexing, partitioning, and query optimization. 

• Implement observability, monitoring, alerting, logging, data quality validation, and reconciliation frameworks to ensure operational excellence and platform reliability. 

• Troubleshoot complex production issues, perform root-cause analysis, and collaborate with SRE and DevOps teams to improve platform stability