Lead Data Architect

Bounteous

1d • Remote

About The Position

This is a data-heavy, hands-on leadership role for someone who can dig deep into complex datasets themselves and guide a team through equally complex problems. We are looking for someone who can not only review others' work but also is a strong individual contributor with senior-level technical caliber who can roll up their sleeves on the hardest analyses, set the technical bar for the team, and unblock analysts when the work gets genuinely difficult.

Requirements

• 9+ years of hands-on data analysis experience, with demonstrated depth (not just breadth) in complex, high-volume datasets
• 2+ years leading or mentoring analysts on technically difficult work, not just project managing
• Expert-level SQL: comfortable with window functions, query optimization, and untangling large/messy schemas without much documentation
• Experience with cloud data warehouse/ lakehouse platforms such as Snowflake and Databricks; ability to work across both during platform transitions is a plus.
• Solid grounding in statistics — experimentation design, hypothesis testing, regression, and knowing when correlation isn't enough
• Experience with a BI/visualization tool (e.g., Tableau, Looker, Power BI), used as one tool among several rather than the primary skill set
• Demonstrated ability to independently solve ambiguous, multi-layered data problems end to end
• Proven ability to communicate complex technical findings clearly to senior, non-technical stakeholders
• Deep, practical fluency with data — someone who remains close to the analysis itself rather than operating purely at a supervisory level
• Strong analytical and statistical judgment, with the ability to identify data quality issues and edge cases that less experienced analysts may overlook
• Technically credible with data engineering counterparts while remaining an effective communicator to business stakeholders
• Builds credibility with the team through the quality and rigor of their own work, in addition to formal mentorship

Nice To Haves

• Direct experience designing and analyzing A/B tests or experimentation frameworks
• Exposure to data engineering concepts (schema design, ETL, data warehousing) sufficient to diagnose upstream issues
• Experience formally managing analysts (performance, growth plans), not just technical mentorship

Responsibilities

• Lead and execute complex, high-stakes analyses — deep-dive investigations, statistical modelling, and multi-source data problems that require real technical depth, not just query-writing
• Guide and unblock the team on difficult technical problems: query optimization, data modeling challenges, messy/ambiguous datasets, and edge cases junior analysts get stuck on
• Write advanced, performant SQL against large and complex datasets (multi-table joins, window functions, query optimization, working with messy or poorly documented schemas)
• Build and maintain robust data models and pipelines in partnership with Data Engineering, and know enough about the underlying infrastructure to reason about data quality issues at the source
• Apply statistical methods (experimentation/A-B testing, regression, cohort and trend analysis) to move beyond surface-level reporting into rigorous, defensible conclusions
• Design and build dashboards and reporting frameworks, but also know when a dashboard isn't enough and a deeper custom analysis is needed
• Set and enforce technical standards for the team — code review, data quality checks, analytical rigor, and documentation
• Mentor analysts by working alongside them on hard problems, not just reviewing finished output
• Translate ambiguous, loosely-defined business questions into structured, technically sound analytical approaches
• Present complex findings to senior stakeholders in a way that's rigorous but accessible
• Own the technical roadmap for the analytics function's tools, data models, and processes
• Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols
• Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets
• Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.)
• Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information

Benefits

• Bounteous is willing to sponsor eligible candidates for employment visas.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed