Senior Python Engineer

February 12

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Nexla

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Nexla is a comprehensive data integration platform designed to streamline the creation of ready-to-use data from various sources and formats, supporting crucial business processes. The platform offers solutions such as ETL/ELT integrations, real-time data streaming, and API management, providing flexibility and scalability for complex data processes. Nexla's user-friendly no-code/low-code interface empowers business users to access and manage data efficiently. It enhances data operations with advanced features like GenAI model readiness and supports seamless data flow between systems, thus eliminating integration backlogs and reducing costs. Trusted by companies like JnJ, Instacart, and AMEX, Nexla delivers scalable solutions for data sharing, data science, and analytics to enhance business productivity and decision-making.

Data Operations • Data Infrastructure • Machine Learning • Artificial Intelligence • Big Data

11 - 50 employees

☁️ SaaS

🏢 Enterprise

💰 $12M Series A on 2021-10

📋 Description

• About Nexla: • Nexla is the leading Integration platform, built with AI, for AI. • We accelerate the development of solutions for GenAI, Analytics, and Inter-company data. • Nexla makes data users and developers up to 10x more productive by delivering a true blend of no-code, low-code, and pro-code interfaces. • The Opportunity: • We are looking for an experienced Senior Python Engineer to join our backend team and help architect, develop, and scale our backend infrastructure. • A successful candidate will be well-versed in designing and building large-scale distributed systems and have deep expertise in Python-based backend development. • This role is crucial to enhancing Nexla’s core platform, enabling robust data transformation, ingestion, and AI-driven workflows.

🎯 Requirements

• 6+ years of experience in backend software development with a strong focus on Python. • Excellent communication skills, with the ability to translate business needs into technical solutions. • Deep understanding and hands-on experience with distributed systems and cloud-based architectures. • Experience working with various data formats (JSON, Parquet, Avro, etc.) and designing efficient data pipelines. • A problem-solving mindset with the ability to work effectively in a team-oriented environment. • Prior experience or strong interest in AI/ML workflows, particularly RAG-based architectures, and Kafka based architecture is a plus but not mandatory.