Data Engineer with Python

About Ascendion Ascendion is a leader in AI-Native platform driven software engineering company that underwrites outcomes, helping businesses innovate faster, smarter, and with greater impact. We partner with Global 2000 clients across North America, UK, Europe, and APAC to solve complex challenges in data, experience design, software product engineering, and workforce transformation. Powered by expert engineers, thousands of AI agents, and our Engineering to the Power of AI™ (EngineeringAI) method, we deliver measurable outcomes that build trust, unlock value, and accelerate growth. Learn more at ascendion.com Ascendion | Engineering to elevate life We have a culture built on opportunity, inclusion, and a spirit of partnership. Come, change the world with us: · Build the coolest tech for world’s leading brands · Solve complex problems – and learn new skills · Experience the power of transforming digital engineering for Fortune 500 clients · Master your craft with leading training programs and hands-on experience Experience a community of change makers! Join a culture of high-performing innovators with endless ideas and a passion for tech. Our culture is the fabric of our company, and it is what makes us unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows everyone to be their best at Ascendion. Python Data Engineer Key Responsibilities: · Python Proficiency: Expert knowledge of Python, including data-centric libraries like Pandas, NumPy, and PySpark. · Big Data Ecosystem: Hands-on experience with handling large data systems (Data Lake etc) · Database Mastery: Advanced SQL skills (CTEs, window functions) and experience with NoSQL systems (Mongo etc). · Cloud Platforms: Experience with major cloud providers (Azure is must) and their data services (e.g., S3, Redshift, BigQuery). · Software Engineering Best Practices: Mastery of Git, unit testing (JUnit, Pytest), and CI/CD pipelines. · Problem-Solving: Proven ability to troubleshoot complex, distributed data issues and optimize query performance. · Communication: Ability to explain technical infrastructure and data lineage to non-technical stakeholders.

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