(Boston, MA- Local Candidate Only)
Title: Senior Data Engineer
Location: Boston, MA - Hybrid Role - We are targeting local candidates that can be in the Boston office 3 days per week.
Client Domain: Financial
Duration: 12 Month + contract (or contract to hire, if desired)
Must have LinkedIn
Max-2-3 pages resume.
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.
