Principal Data Engineer

SS&C is a leading provider of mission-critical, AI-powered technology and services empowering financial services and healthcare organizations to work smarter, faster, and securely. Founded in 1986, SS&C is headquartered in Windsor, Connecticut, and has offices worldwide. More than 23,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.

Job Description

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, scalability, and deployment automation.

• Provide technical leadership, mentorship, and guidance to engineering teams while driving best practices, governance, and continuous improvement initiatives.

Required Experience

• Strong expertise in Java, Spring Boot, REST API development, and Microservices Architecture

• Proficiency in Python is preferred; experience with Node.js is a plus

• Strong hands-on experience with Apache Kafka, Kafka Connect, Kafka Streams, Apache Flink, and AWS MSK

• Extensive experience designing and developing cloud-native applications on AWS

• Solid expertise in Kubernetes, Docker, Terraform/CloudFormation, ECS, and EKS environments

• Strong knowledge of Oracle, PostgreSQL, Amazon Redshift, and Amazon Aurora databases

• Experience with data modeling, database optimization, query tuning, indexing, and performance improvement strategies

• Proven experience developing and maintaining CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI/CD, Maven/Gradle, and SonarQube

• Strong expertise in monitoring, logging, and observability tools including CloudWatch, Prometheus, Grafana, ELK Stack, and related operational frameworks

What Sets You Apart

• Bachelor’s or master’s degree in computer science, Engineering, Information Systems, or a related field

• 8+ years of software engineering or data engineering experience

• 5+ years of hands-on experience with Apache Kafka and event-driven architectures

• 4+ years of experience with Apache Flink and real-time stream processing

• Strong experience designing scalable, fault-tolerant, and highly available distributed systems

• Proven experience leading enterprise-scale platform initiatives and mentoring engineering teams

Join SS&C, where innovation meets global opportunities. Click here to apply.

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Unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.

SS&C Technologies offers a comprehensive total rewards package designed to support your wellbeing, growth, and future. Our benefits include medical, dental, and vision coverage; a 401(k) plan with company match; paid time off, holidays, and parental leave; and professional development reimbursement opportunity.

Applications will be accepted on an ongoing basis until the position is filled.

SS&C Technologies is an Equal Employment Opportunity employer and does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.