Sr. Manager, Analytics Engineering

Betterment•New York City, NY

12d•Onsite

About The Position

Betterment’s Analytics Engineering team turns complex company data into reliable, well-modeled data products supporting analytics, finance, marketing, and other business needs. The team works across the data lifecycle, including transforming and testing warehouse data, operating pipelines, and enabling trusted data to flow to downstream systems. The Senior Manager sets the direction for this work and leads the people and operating model needed to make it reliable at company scale. The role grows a high-performing team of analytics engineers, shapes a roadmap that balances shared foundations with business needs, and ensures data products are accurate, understandable, observable, and useful. The Senior Manager partners with Analytics, Data Platform, Product Engineering, Finance, Marketing, CRM, and Revenue Operations to turn business problems into scalable data capabilities. This role combines strategic leadership with technical judgment. The Senior Manager stays close enough to architecture and implementation to guide important decisions while empowering the team to own execution and outcomes. The position is based out of Betterment’s NYC office. The listed New York City base salary range is $180,000–$210,000; actual salary may vary based on factors including location, experience, and performance. The role may also be eligible for variable compensation through a company incentive bonus.

Requirements

At least 8 years of experience as an analytics engineer and/or data engineer.
At least 3 years of experience directly managing a team of 4 or more analytics/data engineers.
Ability to set technical direction for analytics engineering and coach engineers to lead execution.
Strong expertise in SQL, ETL/ELT using dbt, data modeling, modern data warehousing, and practices for delivering production-quality analytical data products.
Understanding of software engineering practices and workflows, including testing, version control, code review, deployment, monitoring, documentation, and incident management.
Experience working across data, product, engineering, and business teams, translating stakeholder needs into technical requirements.
Experience prioritizing planned work and urgent requests, communicating tradeoffs, and keeping partners aligned.
Curiosity, sound judgment, and a continuous-improvement mindset in a changing data and technology landscape.

Nice To Haves

Experience with Airflow, cloud data warehouses, and reverse-ETL and CRM integrations; experience with equivalent technologies is also valuable.

Responsibilities

Set and communicate the Analytics Engineering vision, roadmap, and priorities, connecting data investments to business outcomes.
Lead, coach, and grow individual contributors; set clear expectations, support career development, and build a healthy, inclusive team culture.
Partner with Analytics and cross-functional leaders to identify trusted datasets and self-service capabilities that can improve workflows and reduce repeated work.
Work with Data Platform and Product Engineering to shape data contracts, upstream changes, warehouse models, and reliable pathways from source data to business-ready products.
Guide the design and evolution of dbt models, Airflow pipelines, data quality, documentation, monitoring, and deployment practices.
Balance roadmap delivery, incoming requests, operational support, and technical health; make tradeoffs visible and align stakeholders on sequencing and scope.
Provide technical direction for analytics engineering while empowering the team to lead implementation and own outcomes.