Data Engineer: Cloud ETL, MongoDB & SQL Pipelines

MATRIX SYSTEMS & TECHNOLOGIES INC

Washington (District of Columbia)

On-site

USD 110,000 - 160,000

Full time

5 days ago
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Job summary

Matrix Systems and Technology, Inc. (MSTi) seeks a Data Engineer to design, develop and support data pipelines across cloud, relational and NoSQL environments in the Washington, DC region.

You will contribute to building scalable data solutions for government and commercial clients. Responsibilities include ETL/ELT workflow development with AWS Glue and Informatica, data ingestion from MongoDB, Aurora/RDS and Oracle, and writing SQL to map source-to-target data.

Qualifications

  • Approximately four to eight years of relevant data engineering experience.
  • Experience with AWS Glue and Informatica.
  • Experience with MongoDB, Amazon Aurora/RDS and Oracle.
  • Strong SQL, data mapping and integration skills.
  • Experience building and troubleshooting ETL/ELT pipelines.
  • Ability to collaborate with application developers, analysts and testing teams.

Responsibilities

  • Design, develop and maintain data ingestion and transformation pipelines.
  • Build and support ETL/ELT workflows using AWS Glue and Informatica.
  • Integrate data from MongoDB, Amazon Aurora/RDS, Oracle and other sources.
  • Develop SQL queries and support source-to-target data mapping.
  • Validate data accuracy and investigate processing failures.
  • Monitor pipeline reliability and document operating procedures.

Skills

Data integration
ETL/ELT pipelines
SQL
AWS Glue
Informatica
MongoDB
Aurora/RDS
Oracle
NoSQL

Tools

MongoDB
Aurora/RDS
Oracle

Job description

Matrix Systems and Technology, Inc. (MSTi) seeks a Data Engineer to design, develop and support data pipelines across cloud, relational and NoSQL environments in the Washington, DC region.

You will contribute to building scalable data solutions for government and commercial clients. Responsibilities include ETL/ELT workflow development with AWS Glue and Informatica, data ingestion from MongoDB, Aurora/RDS and Oracle, and writing SQL to map source-to-target data.

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