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DeWinter Group · Boston, MA

Senior Data Engineer

HybridseniorcontractPosted yesterday
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Stack mentioned

data-engineeringetlapache-kafkaawssnowflakedata-governancesql-serverpostgresqldynamodbobservabilitydatabrickspythonapache-flinkkubernetesdagstersystem-design

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.

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