Data Engineer
4 semanas atrás
São Paulo/SP - Brazil
About the Role:
As a Data Engineer, you will be at the heart of our data-driven initiatives, designing and implementing scalable data pipelines and architectures that drive business insights and innovation. Your expertise in Databricks, Python, and SQL will be crucial in transforming raw data into actionable intelligence, supporting our clients in their journey to leverage data for strategic advantage.
Key Responsibilities:
Build and Maintain Data Pipelines:
Design and develop efficient, scalable data pipelines and architectures using Databricks, Python, and SQL to support various business needs.Optimize Data Systems:
Implement and optimize data processing workflows to ensure high performance and reliability.Collaborate and Communicate:
Work closely with cross-functional teams and clients to understand their data needs and deliver tailored solutions. Excellent communication and consultative skills are essential.Stay Ahead of the Curve:
Continuously improve data processes and explore new technologies to keep our data systems cutting-edge.
What We’re Looking For:
Experience:
4+ years in Data Engineering with a strong foundation in software development, including building and managing data pipelines.Technical Skills:
Proficiency in Databricks, Python, SQL, and Cloud environments is required. Experience with Spark, PowerBI, and MLOps is a plus.Client-Facing Abilities:
While prior consulting experience is not mandatory, any client-facing experience is highly valued.Communication:
Exceptional communication skills and a consultative approach to problem-solving.
Why Join Us?
Impact:
Play a key role in transforming data into valuable insights for our clients, impacting their decision-making and success.Opportunities:
Join a forward-thinking team with opportunities for professional growth and advancement across our locations in Brazil (Sao Paulo, Campinas, Maringa), Costa Rica, and Panama.Innovation:
Work with cutting-edge technologies and contribute to exciting projects that push the boundaries of data engineering.
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