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SeniorГибридПолная занятость

Senior Manager, Data Engineering

Оценка ИИ

Отличная позиция в известном финтехе с прозрачным диапазоном зарплаты, удаленным форматом работы и сильной корпоративной культурой. Высокий балл за стек технологий и социальный пакет.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует сочетания глубоких технических знаний (Spark, AWS, Snowflake) и управленческих навыков. Высокая планка установлена также в области использования AI-инструментов в повседневной работе.

Анализ зарплаты

Медиана195 000 $
Рынок160 000 $ – 240 000 $
Оценка ИИ

Предложенный диапазон ($149k - $222k) полностью соответствует рыночным стандартам для позиции Senior Manager в Нью-Йорке, где медиана составляет около $195k. Верхняя граница диапазона выше среднего, что делает предложение конкурентоспособным.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Manager, Data Engineering position at Stash. With over 8 years of experience in data architecture and a proven track record of leading engineering teams, I am excited about the opportunity to help democratize wealth creation by scaling your data platform. My background in building Spark-based ETL pipelines and managing AWS-based ecosystems aligns perfectly with your current modernization efforts and the transition towards a Snowflake target state.

Throughout my career, I have balanced technical leadership with hands-on contributions, much like the requirements of this role. I am particularly impressed by Stash’s commitment to integrating AI into daily workflows, a practice I have already adopted using tools like ChatGPT and Cursor to enhance code quality and team productivity. I am confident that my experience with dbt, Airflow, and Fivetran, combined with my leadership style focused on ownership and technical excellence, will make a significant impact on your Data team.

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Описание вакансии

Want to help everyday Americans invest and build wealth? Financial inequality is increasing, and too many people are getting left behind. At Stash, we’re passionate about democratizing wealth creation through education, advice, and products that help customers achieve greater financial freedom. We also believe in working smarter—leveraging AI and emerging technologies to move faster, operate more efficiently, and focus our time on solving meaningful problems for our customers.

Join our Data team as a Senior Manager, Data Engineering and play a key role in evolving and scaling the data platform that powers critical business decisions across the company. You’ll lead architectural strategy, strengthen data reliability and governance, and drive modernization efforts that unlock faster analytics, experimentation, and AI-driven innovation in a high-growth fintech environment.

This role blends people leadership with deep technical ownership — ideal for a hands-on leader who enjoys shaping architecture while mentoring and growing a high-performing team.

What you'll do:

  • Define and drive the evolution of our data platform strategy across Fraud, Brokerage, Marketing, Product, Analytics, and Data Science.
  • Lead architectural decisions around distributed processing, warehouse strategy (Snowflake target state), ingestion tooling, and workflow orchestration.
  • Design and scale Spark-based ETL/ELT pipelines supporting batch and selective real-time use cases.
  • Improve automation, reliability, observability, and cost efficiency across our AWS-based ecosystem.
  • Strengthen data governance, lineage, validation, and quality standards across the platform.
  • Lead initiatives to modernize ingestion patterns, including expanding tools like Fivetran and improving workflow maintainability.
  • Contribute directly to architecture, code reviews, and complex problem-solving across Spark, Airflow, DBT, and warehouse layers.
  • Own end-to-end data workflows from ingestion (Postgres and backend systems) through transformation and warehouse delivery.
  • Partner cross-functionally to translate evolving business needs into scalable, production-grade data solutions.
  • Mentor and develop engineers while fostering a culture of ownership, accountability, and technical excellence.

What We're Looking For:

  • 8+ years of experience in data engineering, data warehousing, or data architecture roles.
  • Experience leading or mentoring engineers on small to medium-sized teams.
  • Deep expertise in Spark and distributed data processing systems.
  • Strong experience working within AWS environments.
  • Strong architectural judgment and experience building scalable, production-grade data platforms.
  • Experience designing or evolving modern cloud data warehouse solutions.
  • Strong understanding of distributed systems, data modeling, and ETL/ELT design patterns.
  • Proven hands-on experience with AI tools (e.g., Cursor, ChatGPT, etc.) as a core part of daily workflows, driving productivity and enhancing output quality, alongside a commitment to continuously developing AI expertise
  • Consistent integration of AI into workflows and decision-making, with strong judgment—validating outputs, adhering to Stash guidelines (especially for sensitive data), and owning the quality of AI-assisted work
  • Experience improving platform reliability, performance, and cost efficiency.
  • Excellent cross-functional communication skills.
  • Ability to operate as both a people leader and hands-on technical contributor.

Gold Stars:

  • Experience implementing or migrating to Snowflake.
  • Working knowledge of DBT and analytics engineering best practices.
  • Experience implementing automated ingestion tools such as Fivetran.
  • Experience working in regulated environments (PCI, SOC 2, fintech).
  • Startup or scale-up experience in fast-moving, high-growth organizations.
  • Proven ability to influence architectural direction across multiple engineering teams.

#LI-HYBRID


Our Commitment to Diversity, Equity, and Inclusion

We proudly celebrate the unique qualities that make you you, 365 days a year, and not just because it’s the right thing to do or good for business. We embed the principles and practices of diversity, equity, and inclusion (DEI) into all that we do to prioritize people, a Stash core value, and to ensure Stashers of all backgrounds and experiences can be their authentic selves.

We are also proud to be the first and only venture-backed fintech to join theCEO Action for Diversity & Inclusion™, and as an Equal Opportunity Employer, Stash is committed to building an inclusive environment for people of all backgrounds.

If you require any reasonable accommodations to make your application process more accessible, please reach out to recruiting@Stash.com.

Helping You Invest in Yourself

  • Comprehensive total rewards package, comprising compensation (salary and equity) and health care benefits
  • Complimentary subscription toStash+ account
  • Remote-first work policy – Live and work where you feel the most productive, whether that is in your home, in an office.
  • Flexible PTO
  • Work-from-home equipment stipends; home internet subsidy
  • Paid Parental Leave (offerings for birth giving and non-birth giving parents) Primary & Secondary
  • Enhanced health and wellness benefits through One Medical, Gympass, and Maven Health

External Recognition for Stash

  • Benzinga’s 2023 Best Brokerage for Beginners and Best Robo-Advisor Awards
  • Qorus-Accenture’s 2023 Banking Innovation Awards
  • USA Today and Statista’s 2023 Top 500 Best Financial Advisory Firms
  • Comparably's Best Company Awards: Best Places to Work, Best Company Outlook, and Best Engineering Team for Diversity, Women, Culture, and more! (2023)
  • Fintech Breakthrough Award: Best Personal Finance App (2023)
  • BuiltIn’s Best Places to Work (2022, 2021, 2020, 2019)
  • Forbes Fintech 50 (2021, 2020, 2019)
  • Best Digital Bank, Finovate Awards (2020)
  • Tearsheet Challenge Awards, Best Banking Card Product - Stock-Back® Card, 2020
  • LendIt Fintech Innovator of the Year (2020, 2019)

Salary Range: $149,180 - $222,040

The base salary range represents the reasonably anticipated low and high end of the salary range for this position. Actual salaries will vary and will be based on various factors, such as the candidate’s qualifications, skills, experience and competencies, as well as internal equity and alignment with market data for companies of our size and industry.

\*\*No recruiters, please\*\*

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Навыки

  • AWS
  • Data Architecture
  • Python
  • SQL
  • dbt
  • PostgreSQL
  • Snowflake
  • Airflow
  • Spark
  • ETL
  • Fivetran

Возможные вопросы на собеседовании

Проверка опыта управления и менторства в технической среде.

Опишите ваш подход к балансированию между личным техническим вкладом (hands-on) и управлением командой. Как вы расставляете приоритеты?

Оценка архитектурного мышления и опыта работы с целевым стеком компании.

Какие основные сложности вы видите при миграции крупной платформы данных на Snowflake и как бы вы их решали?

Проверка навыков оптимизации затрат, что указано в требованиях.

Расскажите о вашем опыте оптимизации стоимости владения (TCO) в облачной инфраструктуре AWS для обработки данных.

Оценка соответствия современным требованиям компании к использованию ИИ.

Как именно вы интегрируете AI-инструменты (например, Cursor или LLM) в свой рабочий процесс для повышения эффективности команды?

Проверка понимания специфики финтеха.

С какими вызовами в области управления качеством и безопасностью данных вы сталкивались в регулируемых средах (например, SOC 2)?

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stashinvest
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149 180 $ – 222 040 $