Senior Data Engineer

Numerator / Market Track, LLC; Brasil; Híbrido; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A leading analytics company is seeking a Senior Data Engineer to design resilient data pipelines and enable advanced analytics capabilities. You will collaborate with various teams to ensure data integrity and performance while driving technical strategy and mentoring engineers. The ideal candidate has over 5 years of experience in data engineering, strong skills in Python and SQL, and knowledge of cloud services like AWS or Azure. This role offers a chance to make significant impacts on business outcomes.

Qualificações

• 5+ years of experience in data engineering with large-scale platforms.
• Expertise in Python and SQL for data transformations.
• Experience with cloud-based solutions, especially AWS, Azure, or GCP.

Responsabilidades

• Lead design and scaling of data products.
• Deliver complex, end-to-end data projects.
• Architect and develop pipelines with validation and efficiency.

Conhecimentos

Data engineering experience

Python proficiency

SQL expertise

Data modeling

ETL/ELT design

Orchestration tools (Airflow)

Cloud solutions (AWS/Azure/GCP)

Machine Learning familiarity

Problem-solving

Descrição da oferta de emprego

The Role

As a Senior Data Engineer at Numerator, you will design and build resilient data pipelines, architect infrastructure, and enable advanced analytics and modeling capabilities. You will work closely with Product, Analytics, Data Science, and Engineering teams to ensure the integrity, scalability, and performance of our data systems. Beyond implementation, you will drive technical strategy, mentor engineers, and deliver production-grade solutions with measurable impact.

What You Get to Do

• Lead cross-functional initiatives to design, enhance, and scale data products that power analytics and customer-facing solutions.
• Own and deliver complex, end-to-end projects focused on improving data quality, integrating advanced statistical and machine learning models, and driving measurable business outcomes.
• Architect and develop pipelines with robust validation, quality enforcement, and efficient workflows for model deployment.
• Partner with data scientists to streamline model integration, ensuring reliability and performance in production systems.
• Define and promote engineering best practices, design standards, and technical excellence across the team.
• Mentor and guide junior engineers, fostering technical growth and knowledge-sharing.

What We Require

• 5+ years of experience in data engineering, including designing and maintaining large-scale data platforms, building advanced data pipelines, and implementing production solutions.
• Proficiency in Python and SQL, with expertise in developing efficient, high-quality data transformations.
• Strong background in data modeling, ETL/ELT design, and orchestration tools (especially Airflow), ensuring scalability and integrity.
• Proven track record deploying cloud-based solutions in AWS, Azure, or GCP, with emphasis on resilience and reliability.
• Familiarity with Machine Learning/Statistical Model Development processes and their data dependencies.
• Demonstrated leadership in solving complex problems, with intellectual curiosity, attention to detail, and a focus on business impact.