Cloud Data Engineer

Opportunity Overview
We are seeking a highly skilled Senior Cloud Data Solutions Engineer to drive the design, development, and scaling of data-driven platforms that support advanced analytics, machine learning, and high-value business decisioning. This role is instrumental in shaping next-generation data, trading decisioning, and risk management systems. You will work hands-on across the full data and ML pipeline spanning data engineering, MLOps, and cloud-native development while also influencing architectural direction and mentoring engineering teams. This is an excellent opportunity to work in a modern, collaborative, and innovation-focused technology environment. What You Will Do . Lead by Doing: Design, develop, and review scalable data pipelines, high-performance backend systems, and ML engineering workflows; own projects end-to-end with deep hands-on coding. . Set Technical Direction: Establish engineering best practices in data, ML, and cloud platforms; evaluate modern technologies and drive adoption in alignment with strategic goals. . Cross-Functional Collaboration: Partner with data scientists, business stakeholders, and technology teams to translate requirements into production-grade solutions. . Deliver at Scale: Ensure high-quality execution across data and ML products manage risks, maintain compliance with enterprise standards, and uphold robust data governance and security practices. . Architect for the Future: Contribute to large-scale cloud architectures that support distributed processing, real-time analytics, and next-gen ML capabilities. What You Need to Succeed Must Have . 7+ years designing and building high-performance, data-intensive backend systems with strong knowledge of distributed systems. . 5+ years hands-on experience with big data and distributed processing tools (e.g., Apache Spark, Hadoop, AWS Glue, AWS EMR, Snowflake, Azure Databricks, Azure Data Factory). . Solid understanding of the machine learning lifecycle, including MLOps practices such as model deployment, monitoring, CI/CD, and automated pipelines. . Hands-on expertise with cloud platforms (AWS or Azure) and scalable architectural patterns. . Working knowledge of front-end frameworks (React, Angular) and backend frameworks (FastAPI, Flask, Node.js, or Spring Boot). . Strong communication skills with the ability to explain technical concepts to diverse audiences. . Bachelors degree in Computer Science, Engineering, or related field (Masters/PhD preferred). Nice to Have . Experience with AWS SageMaker, ML model serving, or LLM deployment workflows. . Experience in full-stack development.