MongoDB Engineer - REMOTE

• Posted 5 days ago • Updated 4 minutes ago
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Job Details

Skills

  • MarkLogic
  • Systems Architecture
  • Data Modeling
  • Pattern Recognition
  • Embedded Systems
  • Replication
  • High Availability
  • Failover
  • Scalability
  • Shell
  • Recovery
  • Node.js
  • Java
  • Data Quality
  • Modeling
  • Meta-data Management
  • RDBMS
  • SQL
  • Extract
  • Transform
  • Load
  • ELT
  • Apache Kafka
  • Streaming
  • Python
  • JavaScript
  • Scripting
  • Microservices
  • Spring Framework
  • Amazon Web Services
  • Google Cloud
  • Google Cloud Platform
  • MongoDB
  • ATLAS
  • Cloud Computing
  • Migration
  • Data Security
  • Authentication
  • Encryption
  • Payment Card Industry
  • Database
  • XQuery
  • Health Care
  • Soft Skills
  • Problem Solving
  • Conflict Resolution
  • Analytical Skill
  • Communication
  • Documentation
  • Accountability
  • Leadership

Summary

TITLE - MongoDB Engineer - REMOTE

**CANDIATES MUST COMPLETE ROPES ASSESSMENT FOR THIS ROLE**

REMOTE

This role involves a MarkLogic to MongoDB Migration. They need a REALLY strong, exceptional engineer who has good System Architecture experience (Understanding the whole picture), exceptional communication skills, and cloud migration experience; these are all musts. Need a rockstar who doesn't need handholding and can get into meetings and contribute right away with minimal oversight.

MongoDB Engineer

Description: Looking for a highly skilled MongoDB Engineer with a strong background in developing highly scalable solutions. Must be able to work within a highly functioning team to meet required deadlines.

Technical Skills:

Data Modeling and Schema Design: Proficiency in MongoDB's flexible schema model, validation, access pattern recognition to design appropriate document structures (embedded and normalized models) for optimal read and write performance at scale.

Querying and Aggregation: Proficiency in MongoDB Advanced CRUD operation and complex aggregation pipelines.

Indexing: Knowledge of Database indexing techniques and strategies to maintain, optimize and improve query performance.

Replication and Sharding: Experience in MongoDB's high availability and failover, vertical and horizontal scalability, including replica sets and sharding.

Tooling:

Proficiency with MongoDB suite of products such as, Atlas, Shell and Compass, mongo restore, mongo import, mongo export) and drivers (Node.js, Python, Java, etc.).

Data Quality and Governance: Experience and understanding of data lifecycle, architecture, modeling, metadata, lineage, profiling, monitoring, rule definition, and remediation to ensure data accuracy, consistency, and reliability during migration.

Relational DB Expertise:

Relational Database Knowledge: Understanding of traditional relational database systems and how they work (SQL syntax, schema design, import, indexing operations, data export) is crucial for migrating from traditional databases to MongoDB.

Data Movement Expertise:

ETL: Expertise in ETL/ ELT processes, tools and methods. Knowledge of Pub/Sub, Kafka and other streaming toolsets is a plus.

Programming and Scripting:

Proficiency in languages (Python, JavaScript, Spring boot) for migration scripts and automation. Experienced in developing using Microservices Architecture and Spring boot frameworks.

Cloud Technologies:

Core competency in these cloud platforms and services: AWS, Google Cloud Platform and MongoDB Atlas. Cloud migration strategies and knowledge a must.

Data Security:

Implementing security best practices, including authentication and encryption (At rest, In transit). Experience in multiple options in securing data within a healthcare organization (PHI, PII, and PCI)

Highly Desired:

Mark Logic: Understanding of Mark Logic database and XQuery concepts.

Healthcare Experience: Familiarity with healthcare data and systems. Experience with members, providers, and claims systems and data is most desired.

Soft Skills:

Problem-Solving: Analytical thinking and the ability to diagnose and resolve technical challenges.

Communication: Clearly communicating complex technical concepts to technical and non-technical stakeholders, creating documentation, and coordinating with different teams.

Leadership: Demonstrates accountability and leadership in driving program targets and works together with team members and stakeholders to achieve goals.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91022079
  • Position Id: 2026-49217
  • Posted 5 days ago
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