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A leading technology firm in São Paulo is looking for a Big Data Engineer specialized in Java and Python to develop backend services and work with Big Data technologies. The role involves collaborating with product and design teams to enhance systems handling large data volumes, requiring 3-5 years of relevant experience. This position offers a competitive monthly salary of ~$2,200 USD and a contract duration from September 2025 to March 2026.
Big Data Engineer (Java / Python Backend) - Recomendation Platforms São Paulo, Brazil
Contract Duration : September 2025 – March 2026
Compensation : ~$2,200 USD / month (as FTE)
Develop and enhance backend services using Java or Python, contributing across the full product lifecycle.
Work directly with Big Data pipelines using Hadoop, MapReduce, and Spark (current systems run on MapReduce, with active migration to Spark).
Collaborate with product, design, and client teams to understand user impact and translate requirements into scalable technical solutions.
Improve performance, reliability, and maintainability of large-scale distributed systems.
Apply automation where beneficial and contribute to continuous system improvements.
Communicate technical decisions clearly, including the ability to describe and interpret system diagrams and architectural flows.
3–5 years of experience in backend engineering with strong proficiency in Java / Python.
Hands-on experience with Big Data technologies: Hadoop, Spark, and / or MapReduce.
Ability to build, optimize, and maintain distributed systems that handle large data volumes.
Strong communication skills, especially to explain architecture, data flow, and user impact.
Experience working on consumer-facing or large-scale product environments.
Familiarity with Big Data tooling (e.g., Power BI, data pipelines) is a plus.
Experience with basic automation is helpful (testing is not a core requirement).
Engineers who have real hands-on Big Data experience—not just surface-level exposure.
Professionals who understand how backend decisions affect user experience.
Those with experience in industries similar to large-scale consumer tech, social platforms, AI-driven products, or high-traffic data ecosystems (e.g., recommendation systems, content discovery, digital media platforms).