Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
Пожаловаться
Зарплата и рынок
ЗП не указана
На похожих ролях по рынку
$134к$165кмедиана$195к
49 в выборке
На СНГ рынке: $5.9к/мес ($3.5к - $8.3к)
78
Хорошая вакансия
развернуть
Роль описана четко и сочетает техническое лидерство с практической работой на современном стеке, но зарплата не указана, а обязательные три дня в офисе ограничивают гибкость.
Кликните для подробной информации
Зарплата не указанаСовременный стекПонятная зона ответственностиРегулярная работа в офисеКрупный международный работодатель
Оценка от Hirify AI
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Подключить Plus
Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Technical Lead Data (Databricks/Spark): Leading mixed squads of data engineers and building production data pipelines for priority initiatives within Marsh’s Innovation & Data Office with an accent on hands-on engineering, cloud data platforms, and maintainable architecture. Focus on designing medallion architectures, solving complex data quality and pipeline problems, and translating business requirements into reliable data solutions.
Location: Mexico City, Mexico or Toronto, Canada; hybrid work with at least three days per week in the local office or onsite with clients
Company
Marsh is a global risk, reinsurance, capital, people and investments, and management consulting organization serving clients in 130 countries.
What you will do
Lead a delivery squad of 4–8 data engineers, including employees and contractors.
Set technical direction, decompose work, manage sprint execution, and own squad delivery.
Design data models, medallion architectures, ingestion contracts, and reusable engineering patterns.
Build and debug production pipelines using SQL, Python, and Spark.
Partner with Engagement Leads and business stakeholders to translate business needs into data solutions.
Establish standards for CI/CD, version control, testing, code review, documentation, and operational excellence.
Requirements
5+ years of hands-on data engineering experience, including experience leading or mentoring engineers.
Strong recent proficiency in SQL, Python, and Spark.
Experience with cloud data platforms on AWS, Azure, or GCP; Databricks experience is strongly preferred.
Experience leading mixed teams of employees and contractors.
Fluency with Git, CI/CD, automated testing, infrastructure-as-code, and DataOps.
Clear communication skills for working with both business leaders and engineers.
Nice to have
Experience with Databricks Unity Catalog, Delta Lake, medallion architecture, and Databricks Workflows.
Experience with dbt or similar transformation frameworks.
Knowledge of data lineage, access controls, metadata management, and data quality frameworks.
Background in financial services, insurance, benefits, or consulting.
Experience with unstructured data ingestion, LLM-based tooling, AI-assisted development, or analytics engineering.
Culture & Benefits
Hybrid work combines remote flexibility with office collaboration and professional development.
At least three days per week are expected in the local office or onsite with clients.
Marsh promotes a diverse, inclusive, and flexible work environment.
Office-based teams establish at least one weekly anchor day for in-person collaboration.
Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →