Lead Data Engineer

Balyasny Asset Management

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
Chicago, ILLondon, United KingdomNew York, NY
Posted
22 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $180k
$141k most similar roles pay here $222k

This listing doesn't post a salary. Most similar roles pay $149,106–$211,200.

Based on 240 similar postings.

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About Balyasny Asset Management

Balyasny Asset Management (BAM) is a global multi-manager hedge fund offering diversified investment strategies across equities, macro, commodities, and systematic trading.

Balyasny Asset Management currently has 59 open roles on FindRole.

Listed pay typically runs $175,000–$250,000 across 30 roles with salary data.

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At a glance

TL;DR · Lead Data Engineer

As a Lead Data Engineer, you will provide technical leadership for the platforms, pipelines, and data products that power analytics, applications, and investment decision-making across the firm. You will architect scalable, cloud-first solutions while leading small teams to deliver reliable, analytics-ready datasets. Your daily responsibilities include designing ingestion pipelines, data models, and platform services using Python, SQL, Snowflake, and AWS. You will also drive the evolution of a Data Acquisition Platform featuring APIs, plugins, and AI-enabled workflows for metadata generation and natural-language access. Key technical requirements include experience with NoSQL systems, Airflow orchestration, and time-series data. You will establish automated quality frameworks, manage incident response, and mentor engineers through code reviews. This role solves complex problems involving structured, unstructured, market, and alternative datasets to ensure performance, lineage, and operational resilience for the firm's investment operations.

What you'll do

  • Design and deliver scalable ingestion pipelines, data models, and platform services using Python, SQL, Snowflake, and AWS.
  • Architect reliable solutions for structured, unstructured, and market datasets with a focus on performance and lineage.
  • Drive the evolution of the Data Acquisition Platform including APIs, plugins, and AI-enabled workflows.
  • Establish automated data-quality frameworks covering completeness, freshness, schema integrity, and business-rule validation.
  • Define technical standards for testing, observability, alerting, and incident response across the data estate.
  • Lead root-cause analysis for complex, time-sensitive data incidents to implement durable corrective actions.
  • Mentor engineers through design reviews, code reviews, and technical coaching to shape engineering culture.
  • Translate requirements from analysts and portfolio managers into robust end-to-end data solutions.

What we're looking for

  • Significant experience building and operating production data platforms, pipelines, and analytics-ready data products.
  • Strong Python and SQL skills with experience across relational and NoSQL data systems.
  • Deep experience with Snowflake or comparable modern cloud data warehouses.
  • Strong hands-on experience with AWS data and cloud services to design secure, scalable, and cost-effective architectures.
  • Experience designing and orchestrating production workflows with Airflow or comparable tools.
  • Strong understanding of data modeling, large-scale dataset performance, time-series data, and temporal-query patterns.
  • Demonstrated ability to lead technical projects end-to-end, make architectural decisions, and mentor engineers.
  • Experience with Go, AI/LLM capabilities in workflows, or financial services (preferred).

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