Role OverviewThe Equities Alternative Data team is responsible for sourcing, integrating, curating, and delivering differentiated alternative datasets that support BAM's Equities Long/Short investment teams.
What You Will Do
Design, build, and grow the data platform and pipelines that support alternative-data research and production use cases for Equities L/S teams, own end-to-end dataset onboarding, build scalable ETL/ELT workflows, leverage and extend BAM's in-house data-quality framework, and partner with portfolio managers and data-product stakeholders.
Why It Might Be a Fit
This individual will help design and scale the data infrastructure underpinning our alternative-data offering, and will contribute to standards for dataset documentation, discoverability, governance, entitlement controls, and auditability.
Requirements
- 5+ years of experience in a data-intensive engineering role, building and operating data pipelines, platforms, or data products
- Demonstrable expertise in SQL and databases, particularly time-series, analytical, and large-scale data stores
- Strong programming skills in Python and/or Rust/C++, plus experience with data-manipulation libraries or frameworks such as Pandas, Polars, PySpark, Dask, or similar
- Experience architecting and building scalable ETL/ELT pipelines, including batch processing and, ideally, streaming or near-real-time workflows
- Experience with column-oriented storage and serialization formats such as Parquet and Arrow
- Strong debugging skills across the application and data stack, with demonstrated problem-solving ability in production environments
- Experience with code optimization and performance tuning for large-scale data processing workloads
- Familiarity with distributed-system data components, such as Kafka, Redis, workflow orchestration tools, messaging systems, or caching layers
- Proven ability to work directly with technical and non-technical stakeholders and communicate trade-offs clearly
- Strong ownership mindset, attention to data quality, and ability to deliver in an iterative, business-focused environment
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