Engineering Manager

About the role

We are seeking an Engineering Manager to lead the Data Infrastructure team within the Statsig Experiment division. You will oversee a multidisciplinary group of software engineers, data engineers, and data scientists to build systems that facilitate large-scale experimentation. In this capacity, you will define the technical and scientific direction for data infrastructure that powers experimentation at scale. You will own the end to end lifecycle of complex data platforms, ensuring they meet rigorous standards for performance and reliability. Your leadership will directly influence how product teams design, run, and learn from their experiments. You will translate ambiguous business problems into clear engineering strategies for the team. This role requires a balance of deep technical insight and high level stakeholder management. You will mentor engineers to achieve technical excellence while delivering impactful product outcomes.

Key facts

What you'll do

• Architect and scale data ingestion pipelines that support real time streaming, SDKs, and OpenTelemetry for global experimentation workloads.
• Design and evolve distributed computation systems that execute complex statistical models across cloud and warehouse environments.
• Lead the development of the statistics engine, focusing on Bayesian inference, sequential testing, and variance reduction techniques.
• Collaborate closely with data scientists and engineers to productionize causal inference methodologies into reliable platform components.
• Define and manage the technical roadmap for Statsig Cloud offerings and warehouse native deployment options.
• Partner with customers to uncover experimentation pain points and drive platform improvements that solve real world problems.
• Establish robust data frameworks capable of handling diverse datasets, complex experiment designs, and evolving metric definitions.
• Work with product analytics, feature management, and machine learning infrastructure teams to align experimentation platforms with broader product ecosystems.
• Evaluate and adopt emerging tools in data warehousing such as BigQuery, Snowflake, and Databricks to optimize cost and performance.
• Build processes that enable efficient incident response, observability, and reliability engineering for critical data infrastructure.
• Foster a culture of data driven decision making within the Statsig Experiment division through clear dashboards and insights.
• Ensure that all engineering initiatives comply with security, privacy, and regulatory requirements relevant to experimentation platforms.
• Recruit, onboard, and develop engineers to maintain high performance and innovation within the team.
• Represent the Data Infrastructure team in cross functional discussions to align on company wide experimentation strategy.

Requirements

• Hands on background in data science with a focus on statistics, experimentation, or causal inference.
• Proven experience leading teams of 10 to 15 people building data intensive, statistically rigorous products.
• Demonstrated ability to manage large scale data ingestion and distributed computation across cloud and warehouse environments.
• Deep knowledge of experimentation methods including Bayesian inference, sequential testing, variance reduction, causal effects modeling, and heterogeneous treatment effects.
• Experience translating statistical innovation into system architecture that meets demanding user requirements.
• Strong proficiency in SQL and modern data warehouse query languages for implementing core analytical logic.
• Comfort working with streaming technologies, SDKs, and telemetry standards such as OpenTelemetry.
• Track record of making technical decisions that balance tradeoffs between speed, accuracy, and maintainability.
• Experience interfacing with customers or stakeholders to refine requirements and prioritize technical debt.
• Commitment to maintaining high standards for code quality, testing, and documentation across the team.

Nice to have

• Advanced degree in mathematics, statistics, computer science, economics, or a related quantitative field.
• Experience with product analytics, feature management, or machine learning infrastructure.
• Background in building warehouse native products using BigQuery, Snowflake, Databricks, or similar tools.
• Experience supporting experimentation in marketplaces, B2B, consumer products, or social networks.

Practical notes

-

Compensation: San Francisco Bay Area range is $254,000 - $381,000 total target cash.

• Benefits: Medical, dental, and vision (100% employer-paid premiums on select plans), 401(k) with match, ESPP, 12 weeks paid parental leave, fertility/adoption support, and mental health coaching.
• Perks: Monthly wellness and commuter stipends, quarterly learning and development stipends, and flexible time off.
• Compliance: Pursuant to the San Francisco Fair Chance Ordinance, qualified applicants with arrest and conviction records will be considered. Amplitude is an equal opportunity employer.

This role is based in San Francisco, Canada, and operates under a full time, hybrid engagement model. The selected candidate will split time between remote work and the office, allowing for focused collaboration and team cohesion. The position reports to senior leadership within the Data Infrastructure organization and requires frequent communication with cross functional partners. Travel is generally not required for this role, though occasional meetings may necessitate short distance trips within the region. Candidates must be eligible to work in Canada without sponsorship for this position. The work environment encourages experimentation not only in product but also in how teams are managed and supported. Engineers in this role will have access to cutting edge tools for data management and statistical analysis. The successful manager will balance hands on technical contributions with people leadership responsibilities. Professional growth is supported through structured learning and development stipends provided quarterly. The company is committed to maintaining an inclusive workplace that values diverse perspectives and backgrounds.