Data Engineer with Mongo DB

Job Title : Data Engineer with Mongo DB

Location : Charlotte, NC/Plano, TX

Must Have Technical/Functional Skills

Primary Skill: Data Engineer

Secondary: Mongo DB

Experience: Minimum 10 years

Key Responsibilities:

• MongoDB Database Management:

Designing, implementing, and managing MongoDB database architectures, including schema design, indexing, replication, sharding, and performance optimization for large-scale data.

Data Pipeline Development:

Building and maintaining robust ETL/ELT (Extract, Transform, Load) pipelines for ingesting, transforming, and loading structured and unstructured data from diverse sources into MongoDB and other data platforms.

• Performance Optimization:

Optimizing MongoDB queries, aggregation pipelines, and overall database performance to ensure efficient data processing and retrieval.

• Data Integrity and Security:

Ensuring data integrity, quality, and security by implementing appropriate validation, monitoring, access controls, and encryption measures within MongoDB and related systems.

• Collaboration and Integration:

Working closely with application developers, data scientists, data analysts, and DevOps teams to understand data requirements, integrate MongoDB with other systems and cloud services (e.g., GCP, AWS, Azure), and support data-driven applications.

• Troubleshooting and Monitoring:

Monitoring data pipeline performance, troubleshooting issues, and implementing solutions to ensure data reliability and availability.

• Documentation:

Creating and maintaining documentation for data pipelines, database schemas, and data engineering processes.

Required Skills and Qualifications:

• Strong MongoDB Expertise:

In-depth knowledge of MongoDB's features, including document modeling, aggregation framework, indexing, sharding, and administration.

• Programming Proficiency:

Strong programming skills in languages like Python, Java, or Node.js, particularly with MongoDB drivers and related libraries.

• Data Pipeline Tools:

Experience with data pipeline tools and technologies such as Apache Spark, Airflow, Kafka, or cloud-native data services.

• Cloud Platform Experience:

Familiarity with cloud platforms (e.g., Google Cloud Platform, AWS, Azure) and their data-related services.

• Data Modeling and Design:

Ability to design efficient and scalable data models for NoSQL databases.

• Problem-Solving and Analytical Skills:

Strong aptitude for troubleshooting data-related issues and optimizing data systems.

• Communication and Teamwork:

Excellent communication and collaboration skills to work effectively with cross-functional teams.

Domain Knowledge: Banking and Payments