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

Location: Waltham MA - 10 CityPoint

 

About the Role 

We are seeking a highly skilled and hands-on Principal Data Engineer to lead the design, development, and deployment of scalable AI/ML data platforms, distributed data processing systems, and cloud-native data services. This role requires deep expertise in Python and Java-based backend engineering, microservices architecture, machine learning pipelines, distributed systems, cloud-native platforms, Kubernetes, and AWS technologies. 

The ideal candidate will have extensive experience building enterprise-scale data platforms, developing production-ready ML pipelines, implementing scalable microservices, and driving engineering best practices. This role will collaborate closely with Product, Architecture, Data Science, Application Development, Analytics, SRE, and DevOps teams to deliver highly scalable, reliable, and intelligent 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 AI/ML data platforms, distributed data processing systems, and cloud-native applications.  

• Design and implement end-to-end ML pipelines including data ingestion, feature engineering, model training, validation, deployment, monitoring, and automated retraining.  

• Build scalable batch and streaming data pipelines using technologies such as Apache Kafka, Apache Flink, Spark, or similar distributed processing frameworks.  

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

• Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding generation services, semantic search capabilities, and vector database integrations.  

• 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, containerized applications, and ML deployment workflows using Kubernetes, Docker, Terraform/CloudFormation, ECS/EKS, and AWS services including EC2, S3, Lambda, Redshift, Aurora, RDS, Glue, CloudWatch, and MSK.  

• Design optimized relational, NoSQL, and vector data models using PostgreSQL, MongoDB, Redshift, Aurora, Milvus, Pinecone, Chroma, or similar technologies, including performance tuning, indexing, partitioning, and query optimization.  

• Troubleshoot complex production issues, perform root-cause analysis, and collaborate with SRE and DevOps teams to improve platform stability, scalability, deployment automation, and ML operational workflows.  

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

 

Required Experience  

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

• Experience building production-grade AI/ML platforms, ML pipelines, and distributed data processing applications.  

• Strong understanding of ML SDLC, MLOps, model deployment, and productionizing Python/Java applications.  

• Hands-on experience with Apache Kafka, Kafka Connect, Kafka Streams, Apache Flink, Spark, Airflow, or similar distributed data processing technologies.  

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

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

• Experience with ML frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn.  

• Strong knowledge of Oracle, PostgreSQL, Amazon Redshift, Amazon Aurora, MongoDB, and vector databases such as Milvus, Pinecone, or Chroma.  

• Experience with data modeling, feature engineering, database optimization, query tuning, indexing, partitioning, and performance improvement strategies.  

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

• Strong expertise in monitoring, logging, and observability tools including CloudWatch, Prometheus, Grafana, ELK Stack, Splunk, and OpenTelemetry.  

• Strong Linux proficiency and software engineering best practices. 

 

What Sets You Apart (preferred qualifications) 

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field.  

• 8+ years of software engineering, data engineering, or AI platform engineering experience.  

• Experience building scalable ML pipelines, feature engineering workflows, and enterprise AI platforms.  

• Experience with Generative AI, Retrieval-Augmented Generation (RAG), LLM deployment, embedding pipelines, and semantic search technologies.  

• Experience with ML orchestration frameworks such as Kubeflow, MLflow, Airflow, or similar platforms.  

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

• Experience leading enterprise-scale platform initiatives and mentoring engineering teams.  

• Excellent problem-solving, communication, architectural, and technical leadership skills. 

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. 

 

Actual base salary will vary based on several factors, including but not limited to relevant skills, prior experience, education, demonstrated performance, and geographic location.

Massachusetts: The expected base salary for the position is between 160,000 USD to 170,000 USD. 

 

 

 

 

 

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.