Senior Software Engineer, Strategy Research Analytics
Leads design and evolution of analytics infrastructure for research reporting, owning pipelines, datasets, and platform standardization. Collaborates with data scientists using Python, SQL, distributed engines like Presto/Spark. Requires 6+ years in data infrastructure.
200k – 255k
Remote6+ YOEData Engineering
About the role
Responsibilities
Own implementation and on-going operation of recurring analytics pipelines (e.g., Airflow DAGs) including monitoring, alerting, and reliability improvements
Lead architectural evolution of the analytics platform, including schema standardization, DAG consolidation, and modernization of legacy workflows
Drive cross-team technical alignment when consolidating duplicated or inconsistent analytics outputs
Build and maintain base analytics tables and metrics with strong schema discipline and reproducible computation
Define and implement reliability standards (SLOs, observability patterns, runbooks) adopted across analytics pipelines
Improve transparency and usability through documentation, discoverability, and clear data contracts
Optimize distributed compute and SQL query performance; design data layouts (partitioning, file sizing) for columnar storage
Requirements
Bachelor's degree in Computer Science or equivalent professional experience
6+ years of experience building and operating analytics or data infrastructure systems
Strong proficiency in Python and SQL
Deep experience with distributed query engines and large-scale compute systems
Demonstrated ownership of large-scale or mission-critical data infrastructure
Strong data modeling expertise, including schema design, partitioning strategy, and reproducibility considerations
Expertise in metadata management, data lineage, and applying robust data governance principles
Preferred Qualifications
Experience leading architectural migrations or major refactors of data platforms
Familiarity with AWS cloud technologies and on-prem compute clusters (e.g., Slurm, SSH, Unix)
Exposure to quantitative research or machine learning environments
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200k – 290k
On-site2+ YOEData Engineering
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DecagonNew York, NY
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DecagonSan Francisco, CA
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200k – 400k
On-site5+ YOEData Engineering
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ForgeNew York, NY
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