Senior Lead Data Engineer (AWS)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior Lead Data Engineer (AWS): Designing and operating scalable cloud-based data pipelines to build the organization's data and analytics foundation with an accent on reliability, performance, and cost-effectiveness. Focus on building complex datasets using Python, PySpark, and Databricks on AWS to enable high-quality data delivery across the organization.
Location: Hybrid in Guadalajara, Jalisco, Mexico
Company
A global digital transformation and technology consulting firm focused on AI and data engineering.
What you will do
- Design, develop, and operationalize scalable and performant cloud-based data pipelines.
- Build and maintain large, complex datasets that meet functional and non-functional business requirements.
- Apply database management best practices, including logical data modeling and physical database optimization.
- Implement and enhance data quality checks to ensure the accuracy and integrity of pipelines.
- Collaborate with data analysts and scientists to enhance data platform capabilities.
- Participate in on-call support rotations to resolve critical issues and improve platform reliability.
Requirements
- 5+ years of experience designing and operationalizing data pipelines for complex datasets.
- 3+ years of experience with Python and PySpark for large-scale data processing.
- 3+ years of experience building data solutions specifically on AWS.
- Hands-on experience transforming and processing data using Databricks.
- Strong proficiency in advanced SQL and working with structured/unstructured data (JSON).
- Experience using Git and CI/CD practices for platform development.
Nice to have
- Experience with Power BI or similar business intelligence and visualization tools.
- Familiarity with modern data lake and data warehouse architectures.
- Experience implementing observability, monitoring, and alerting for data pipelines.
- Exposure to streaming data technologies or near real-time processing.
- Experience working in a fast-growing SaaS or platform-focused environment.
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