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.