Senior Data Engineer

Senior Data Engineer This role is with a DeWinter Financial Services Partner Boston, MA - Hybrid Role - We are targeting local candidates that can be in the Boston office 3 days per week. 12 Month + contract (or contract to hire, if desired) You will be responsible for building and evolving the firm's next-generation data platform. The team is focused on designing and implementing scalable data pipelines that move data from operational systems into a centralized data platform built on Kafka, Iceberg, AWS, and Snowflake technologies. This is a hands-on engineering role working on large-scale data ingestion, streaming architectures, data quality, and platform capabilities that support teams across the organization. What You'll Do • Design, build, and enhance scalable data pipelines supporting high-volume data ingestion and processing. • Develop and maintain streaming and batch data solutions using modern data platform technologies. • Build integrations that move data from source systems such as SQL Server, PostgreSQL, DynamoDB, and other operational platforms into Acadian's data ecosystem. • Contribute to the evolution of Acadian's Kafka, Iceberg, and cloud-native data platform initiatives. • Partner with platform engineering, infrastructure, security, and application teams to deliver reliable and scalable solutions. • Improve data quality, observability, monitoring, and operational reliability across the platform. • Leverage AI-assisted development tools as part of the engineering workflow while maintaining strong engineering judgment and code quality standards. • Work with large-scale datasets, including multi-terabyte tables and high-volume event streams. Required Qualifications • 5+ years of experience in Data Engineering, Platform Engineering, or Data Infrastructure Engineering. • Hands-on experience building and supporting production data pipelines. • Experience working with large-scale data platforms and high-volume datasets. • Experience with Kafka or similar event-streaming technologies. • Experience with cloud-based data platforms in AWS. • Experience working with modern data storage technologies such as Iceberg, Snowflake, Databricks, or similar platforms. • Experience developing in Python or another modern programming language. • Ability to explain technical decisions, architecture, and implementation details of systems you have personally built. Preferred Qualifications • Apache Flink experience. • Kubernetes or containerized platform experience. • Iceberg implementation experience. • Snowflake administration or engineering experience. • Dagster experience. • CDC, event streaming, or real-time data processing experience. • Experience building cloud-native data platforms. • Financial services experience (nice to have, not required). What Success Looks Like • Quickly contributes to the team's Kafka and Iceberg initiatives. • Builds and enhances production-grade data pipelines. • Demonstrates ownership of engineering solutions from design through deployment. • Operates effectively in a small, highly collaborative engineering team. • Can clearly articulate system design decisions and implementation tradeoffs.