MEAN Stack Data Engineer

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.