MEAN Stack Data Engineer

3 days ago

Pune, India Codvo.ai Full time

Job Description: Data Engineer – MEAN stack About Us At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology. Role Overview  We are looking for a highly skilled Full Stack Data Engineer with expertise in MEAN Stack to design, develop, and optimize end-to-end applications, and analytics solutions. This role combines strong cloud platform expertise, and software engineering skills to deliver scalable, production-grade solutions. Key Responsibilities  Design and develop applications on MEAN Stack. Mentor and assist team members towards common objective Implement CI/CD pipelines for MEAN Stack workflows using GitHub Actions, Cloud DevOps, or similar. Build and maintain APIs, dashboards, or applications that consume processed data (full-stack aspect). Collaborate with data scientists, analysts, and business stakeholders to deliver solutions. Ensure data quality, lineage, governance, and security compliance. Deploy solutions across cloud environments (Azure/AWS/GCP). Required Skills & Qualifications  Core MEAN Stack Skills: Strong in MEAN Stack SQL. Front End (AngularJS), Backend (NodeJS, Express.JS), HTML, CSS, Bootstrap. Data Layer (Mongo DB/Postgres/MySQL), Cloud (Azure) Programming language - Java Script, Type Script Framework/design patterns - MVC/MVVM. Programming & Full Stack: Python (mandatory), SQL (expert). Exposure to Java/Scala (for Spark jobs). Knowledge of APIs, microservices (FastAPI/Flask), or basic front-end (React/Angular) is a plus. DevOps & CI/CD: Git, CI/CD tools (GitHub Actions, DevOps, Jenkins). Containerization (Docker, Kubernetes is a plus). Data Engineering Foundations: Data modeling (OLTP/OLAP). Batch & streaming data processing (Kafka, Event Hub, Kinesis). Data governance & compliance (Unity Catalog, Lakehouse security). Nice-to-Have  Experience with machine learning pipelines (MLflow, Feature Store). Knowledge of data visualization tools (Power BI, Tableau, Looker). Exposure to Graph databases (Neo4j) or RAG/LLM pipelines. Qualifications  Bachelor’s or Master’s in Computer Science, Data Engineering, or related field. 4–7 years of experience in data engineering, with deep expertise in MEAN Stack. Soft Skills  Strong problem-solving and analytical skills. Ability to work in fusion teams (business + engineering + AI/ML). Clear communication and documentation abilities.

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