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HeadУдалённоПолная занятость

Manager of Data

Оценка ИИ

Интересная руководящая позиция в социально значимой компании с фокусом на AI. Предлагает большую автономию, удаленный формат работы и возможность реально влиять на развитие функции данных.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует сочетания глубоких технических знаний (dbt, SQL, инфраструктура) и развитых навыков управления людьми в распределенной среде. Основная сложность заключается в необходимости выстраивать процессы с нуля в новой для компании позиции.

Анализ зарплаты

Медиана110 000 $
Рынок85 000 $ – 140 000 $
Оценка ИИ

Указанный диапазон соответствует рыночным ставкам для позиций Data Manager в Латинской Америке и Канаде при работе на американские компании. Уровень компенсации сильно зависит от конкретной страны проживания кандидата.

Сопроводительное письмо

I am writing to express my strong interest in the Manager of Data position at Correlation One. With a background that bridges both data engineering and analytics, I am excited by the opportunity to lead your distributed team of engineers and analysts. I have extensive experience not only in managing technical workflows using dbt and SQL but also in mentoring team members and aligning data initiatives with strategic business goals.

Throughout my career, I have focused on transforming manual processes into automated, scalable solutions and partnering with product managers to prioritize high-impact projects. I am particularly drawn to Correlation One's mission of creating equal access to data-driven jobs and would welcome the chance to apply my leadership skills to help your team build the sustainable data infrastructure needed to support your global programs and enterprise clients.

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Присоединяйтесь к Correlation One, чтобы возглавить команду данных и формировать будущее экономики искусственного интеллекта!

Описание вакансии

Correlation One develops workforce skills for the AI economy

Enterprises and governments work with us to develop talent and close critical data, digital, and technology skills gaps. Our global programs, including training programs and data competitions, also empower underrepresented communities and accelerate careers.

Our mission is to create equal access to the data-driven jobs of the future. We partner with top employers and government organizations to make that a reality, including Amazon, Coca-Cola, Johnson & Johnson, the U.S. State Department, and the U.S. Department of Defense.

Our skills training programs are 100% free for learners and are delivered virtually by industry experts to minimize traditional barriers to career advancement. We take pride in fostering supportive, human-led, group learning environments that build technical proficiency and confidence in participants.

Join us and let's shape the AI Economy together!

The Role

We're hiring a Manager of Data to lead our data team. This is a group of engineers and analysts who build and maintain the data infrastructure, pipelines, reporting, and analytical work that powers Correlation One's operations and client delivery.

This is a new role, not a backfill and there's a real opportunity to shape the function's direction. You'll inherit a team of 5–6 engineers and analysts distributed across multiple countries and time zones. They deliver reliably and have built an impressive operational footprint of pipelines, compliance monitoring, automated reporting, client deliverables, etc. What's been missing is someone whose full-time job is to lead the team, develop its people, and make sure the work is pointed in the right direction.

What You'll Do

  • Manage and develop the team. You'll run 1:1s, shape career paths, give honest feedback, and build a team culture that balances high standards with low ego. You'll also own hiring as the team evolves.
  • Own the technical direction. Decide when something is being built the expedient way versus the sustainable way. Help the team ask better questions, structure analyses well, and produce work that actually drives decisions. Guide how the data platform and the team's analytical capabilities evolve together.
  • Decide what the team works on, and what it doesn't. The team's backlog today is largely shaped by incoming requests from stakeholders. You'll be the person who evaluates that work against strategic value, pushes back where appropriate, and protects capacity for longer-arc investments. This means partnering closely with our Data Product Manager to negotiate priorities. You own the "how" and "how much," they own the "what" and "why."
  • Drive operational work toward automation. A meaningful chunk of the team's time goes to recurring manual processes. The pattern we want to follow: identify what's manual, automate it, recover the capacity. You'll find those opportunities and make sure they get done.
  • Be client-aware. Our work supports enterprise clients directly. You should be comfortable understanding client needs, translating them into data requirements, and occasionally representing the data function in client-adjacent conversations.

What You'll Walk Into

A distributed team that's been delivering a lot without dedicated management. They've built real operational value, but they've also been running without someone actively shaping priorities, driving technical investments, and developing people full-time. This isn’t a backfill but a new capability you'd be building.

You'll partner with a Data Product Manager who brings business and stakeholder needs to the team. Together, you'll prioritize those needs, identify the right solutions, and decide how to sequence the work. Getting that partnership right will be one of the most important parts of the role.

You'll report to an SVP who understands the data domain deeply but is stretched across multiple functions and needs someone to fully own the data team's leadership.

Your First 90 Days

Get to know the team and their work. Understand how work enters the system, where time goes, and where the friction is. Build relationships with the Data Product Manager and key Ops stakeholders. Start making calls on what the team should keep doing, do less of, and invest in. Your early wins will come from bringing clarity and focus, not from shipping something new.

What We're Looking For

  • People management experience. You've actually managed people, including hiring, developing, giving hard feedback, and making tough calls. Not just led projects, but owned a team's performance and growth.
  • Technical credibility in the data space. You have a background that spans both data engineering and analytics. You can review a dbt model, help an analyst turn a vague question into a structured approach, and make sound calls on how to build things sustainably. Familiarity with dbt, SQL, warehouse modeling, and pipeline orchestration is key, but so does knowing what makes a convincing analysis.
  • Prioritization judgment. Your job is to figure out what matters most, what can wait, and what should stop. This requires understanding business context, not just technical work.
  • Strong communication and stakeholder skills. You'll partner with product, operations, and occasionally client-facing teams. You need to explain technical tradeoffs to non-technical stakeholders and push back on requests without damaging relationships.
  • Comfort with ambiguity. You're not walking into a well-defined playbook. You'll need to assess, build your own understanding, and start making calls.

Things That Would Give You a Head Start

Experience managing distributed or remote teams across time zones. Familiarity with Terraform, GitHub Actions, or Looker. A background in consulting or client-facing data work. None of these are requirements but they'd shorten your onboarding time.

Where You Are

This role is remote and is open to applicants in Latin America and Canada. Work hours must be compatible with Eastern Standard Time.

How we support our people

  • Insurance or subsidies based on country
  • Retirement plan based on country
  • Unlimited Time Off, with a minimum time off recommendation
  • Company-paid holidays
  • Official company-wide holiday for the last week of the calendar year
  • Access to free data skills training through our programs
  • A company culture that empowers individuals and embraces diversity through its core mission

The compensation range for this position is specific to location and takes into account the wide range of factors that are considered in making compensation decisions. These factors include (but are not limited to) location, experience, education and skill sets.

Correlation One’s Commitment

Correlation One is proud to be an Equal Opportunity Employer and is committed to providing equal opportunity for all employees and applicants. Correlation One provides a work environment free of discrimination and harassment. Employment decisions at Correlation One are based solely on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, or any other status protected by the laws or regulations in the locations where we operate. We encourage applicants to bring their unique skills, experiences, and outlook to our work environment.

Correlation One is committed to the full inclusion of all qualified individuals. In keeping with our commitment, Correlation One strives to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidates@correlation-one.com.

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Навыки

  • Stakeholder Management
  • Terraform
  • SQL
  • Looker
  • dbt
  • GitHub Actions
  • Data Engineering
  • Data Analytics
  • People Management

Возможные вопросы на собеседовании

Проверка опыта управления и развития талантов в технической команде.

Расскажите о случае, когда вам пришлось давать сложную обратную связь члену команды. Как вы это сделали и каков был результат?

Оценка способности балансировать между скоростью и качеством разработки.

Как вы определяете, когда стоит выбрать быстрое временное решение, а когда — инвестировать в долгосрочную архитектуру? Приведите пример.

Проверка навыков взаимодействия с продуктовыми менеджерами и управления ожиданиями.

Как бы вы подошли к разрешению конфликта приоритетов между запросами стейкхолдеров и необходимостью технического долга или автоматизации?

Оценка технической экспертизы в современном стеке данных.

Опишите ваш опыт работы с dbt и моделированием данных в хранилище. Какие лучшие практики вы внедряли для обеспечения качества данных?

Проверка навыков работы в удаленном формате.

Какие методы вы используете для поддержания командной культуры и синхронизации работы в распределенной команде, работающей в разных часовых поясах?

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