Technical Manager, Strategy Research Analytics

Remote, United StatesFull-TimeManagerResearch

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Recruit, mentor, and develop a diverse team of engineers and data specialists, starting with a small core team that will grow to meet the evolving needs of the organization. Build capacity not only to maintain existing pipelines but also to develop and execute on a forward-looking vision for a scalable, world-class analytics platform
Work with existing stakeholders to define and communicate a long-term strategy for analytics infrastructure and enablement, building a vision that solves real-world problems for our data scientists and extends toward a standardized, industry-class analytics platform
Lead team execution in a complex, fast-paced research environment, reducing friction and optimizing workflows
Influence laterally across engineering and research teams to align roadmaps, shape priorities, and drive shared goals
Ensure robust communication of team progress, creating transparency and credibility with senior stakeholders
Oversee consistent, well-documented, and queryable data models that power research today, and extend these frameworks toward the broader vision of a unified analytics platform

Bachelor’s degree in Computer Science or equivalent professional experience
3+ years of proven experience managing geographically distributed software engineering teams
3+ years of experience managing engineering or data teams focused on analytics or data infrastructure
Demonstrated success managing through ambiguity, influencing without direct authority, and leading complex cross-team initiatives
Exceptional stakeholder management and communication skills, capable of clearly articulating vision, progress, and impact
Proven ability to attract, hire, mentor, and retain exceptional engineering talent
Product-focused mindset, with experience shaping product vision, defining roadmaps, and delivering high-impact platform solutions
Strong background in modern data infrastructure and modeling (e.g., SQL, Presto, Spark, Dask, Polars)
Strong understanding of query optimization and performance tuning in SQL and experience with columnar storage formats (e.g., Parquet, ORC)
Demonstrated experience designing normalized and denormalized data structures for analytical workloads

Familiarity with AWS cloud technologies and on-prem compute clusters (e.g., Slurm, SSH, Unix)
Familiarity with Airflow for data orchestration pipelines
Exposure to quantitative research or machine learning environments
Experience managing operationally critical, high-availability systems, ensuring precision, reliability, and robustness
Expertise in metadata management, data lineage, and applying robust data governance principles