Data Engineer, Python, PySpark, Databricks

🔥 49 minutes ago

🌐 Colombia, Argentina – Remote

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💵 $24k - $57.6k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🔙 Backend Engineer

👻 Ghost score 0%

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Devsu

51 - 200 employees

🤝 B2B

🏢 Enterprise

☁️ SaaS

B2B • Enterprise • SaaS

Devsu is a technology services company that provides a range of strategic solutions to help clients scale their operations, enhance efficiency, and drive innovation. The company specializes in staff augmentation, dedicated teams, and custom development, leveraging elite tech talent to meet the specific needs of each project. Devsu offers services in quality assurance, cloud engineering, AI prototyping, and data analytics, among others, ensuring high-quality and scalable solutions. By acting as an integrated partner, Devsu helps businesses achieve faster development cycles and better project outcomes with timezone-aligned teams. With a focus on cutting-edge technology and streamlined processes, Devsu empowers businesses to transform their vision into reality.

📋 Description

• Design, build, and support scalable data pipelines using Python, Apache Spark, PySpark, and Databricks • Modernize and migrate legacy data processing workloads to secure, cloud-native platforms • Build and maintain batch data ingestion pipelines from structured and unstructured sources • Integrate data from REST APIs, SharePoint, document repositories, enterprise applications, and cloud platforms • Implement data quality, monitoring, observability, and operational controls • Optimize data workloads for performance, scalability, reliability, and cost efficiency • Develop document extraction, classification, metadata enrichment, and automation pipelines • Apply software engineering practices including Git, CI/CD, automated testing, and code reviews • Build, deploy, troubleshoot, and maintain production ETL/ELT pipelines • Collaborate with architects, developers, tax subject matter experts, and platform teams • Analyze existing codebases and identify opportunities to improve maintainability, security, and reliability • Use AI-assisted development tools to build, review, test, and maintain data pipeline code

🎯 Requirements

• 3+ years of experience in data engineering • Strong Python development experience • Strong Apache Spark and PySpark experience • Hands-on experience with Databricks • Strong SQL and data modelling skills • Experience building, testing, deploying, and troubleshooting production ETL/ELT pipelines • Experience with Git-based source control and CI/CD pipelines • Experience consuming REST APIs for data ingestion, including authentication, pagination, and failure handling • Experience writing automated tests for data pipelines • Strong understanding of data quality, reliability, and data engineering best practices • Strong problem-solving, communication, and collaboration skills • Experience with Azure cloud services and modernising legacy data pipelines • Experience with document processing, intelligent document extraction, or unstructured data • Familiarity with AI-assisted development tools such as Codex, GitHub Copilot, or similar • Experience with streaming data pipelines or large-scale data repositories • Ability to analyse unfamiliar codebases, identify gaps and trade-offs, and propose practical improvements

🏖️ Benefits

• A stable, long-term contract with opportunities for career growth • Private health insurance • A remote-friendly culture that promotes work-life balance • Continuous training, mentorship, and learning programs • Free access to AI training resources and state-of-the-art AI tools • Flexible Paid Time Off (PTO) policy and paid holiday days • Challenging, world-class software projects for clients in the US and LatAm • Collaboration with talented software engineers in Latin America and the US • Diverse work environment

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