Principal Data Engineer

Principal Data EngineerLocations: Waltham, MA - HybridAbout the RoleWe 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.How You Will Make an ImpactLead 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 ExperienceStrong expertise in Java, Spring Boot, REST API development, and Microservices ArchitectureProficiency in Python is preferred; experience with Node.js is a plusStrong hands-on experience with Apache Kafka, Kafka Connect, Kafka Streams, Apache Flink, and AWS MSKExtensive experience designing and developing cloud-native applications on AWSSolid expertise in Kubernetes, Docker, Terraform/CloudFormation, ECS, and EKS environmentsStrong knowledge of Oracle, PostgreSQL, Amazon Redshift, and Amazon Aurora databasesExperience with data modeling, database optimization, query tuning, indexing, and performance improvement strategiesProven experience developing and maintaining CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI/CD, Maven/Gradle, and SonarQubeStrong expertise in monitoring, logging, and observability tools including CloudWatch, Prometheus, Grafana, ELK Stack, and related operational frameworksWhat Sets You ApartBachelor's or master's degree in computer science, Engineering, Information Systems, or a related field8+ years of software engineering or data engineering experience5+ years of hands-on experience with Apache Kafka and event-driven architectures4+ years of experience with Apache Flink and real-time stream processingStrong experience designing scalable, fault-tolerant, and highly available distributed systemsProven experience leading enterprise-scale platform initiatives and mentoring engineering teams