Acadian Asset Management LLC-posted 4 months ago
Full-time • Senior
Boston, MA
251-500 employees

Building on a multi-decade history in quantitative equity, Acadian has expanded its reach into multi asset class, alternative equity, and systematic credit. The investment data engineering function will build a platform that will expand our data capabilities to operate at significant scale across a broad array of asset classes. We’re looking for a senior contributor to help design, build and support a data platform that will drive our investment process. Acadian supports a hybrid work environment, employees are on-site in the Boston office 3 days a week.

  • Design & build a highly scalable, cloud-native data platform on AWS, leveraging diverse storage formats, high-performance compute, and containerized workloads.
  • Develop & optimize pipelines to rapidly integrate new datasets and derived metrics with speed, reliability, and scalability.
  • Architect & deploy scalable services by building REST APIs, containerizing workloads, and orchestrating deployments in Kubernetes for high availability and elasticity.
  • Collaborate with portfolio managers and researchers to translate investment needs into technical specifications and data solutions that directly support the investment process.
  • Design & build the business logic layer that transforms raw data into investment-ready insights, enabling researchers and portfolio managers to focus on alpha generation.
  • Integrate with investment systems by participating in design reviews, promoting adoption, and ensuring smooth interoperability.
  • Build domain expertise in investment data particularly in the quantitative investing space and address the unique challenges of working with financial data.
  • Maintain mission-critical operations by managing daily production workflows and ensuring platform health with metrics, logging, and distributed tracing.
  • Engineer for excellence by delivering well-tested, extensible, and high-quality solutions.
  • Bachelor’s degree in mathematics, science, or engineering with a strong academic record; CFA charter a plus.
  • Background in the quantitative investing space, with knowledge of financial data and its associated challenges—including timeliness, quality, and integration across varied sources.
  • Analytical, creative, and collaborative personal qualities, with the drive and humility to tackle complex problems and deliver results.
  • Experience with Python (Polars, Pandas, NumPy), SQL.
  • Familiarity with AWS (S3, EC2, ECS), Terraform, Kubernetes for automated, scalable deployments.
  • Experience in REST API design and integration at scale.
  • Knowledge of metrics, logging, distributed tracing for performance and reliability.
  • Familiarity with data systems such as Apache Iceberg, Delta Lake, Spark, Databricks, PostgreSQL, DynamoDB, Redis.
  • Experience with workflow orchestration tools like Dagster, Airflow.
  • Understanding of data modeling, profiling, performance tuning, and full SDLC best practices.
  • Flexible hybrid work environment.
  • Strong benefits package.
  • Casual but focused office culture.
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