

Mondo
Senior Data MDM Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data MDM Engineer, contract-to-hire for 3-6 months, paying $50-60/hr. Remote work is required during EST hours. Key skills include Python, AWS (S3, Lambda), ETL/ELT pipelines, and API integration. Experience in MDM and data architecture is essential.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
480
-
ποΈ - Date
June 13, 2026
π - Duration
3 to 6 months
-
ποΈ - Location
Remote
-
π - Contract
W2 Contractor
-
π - Security
Unknown
-
π - Location detailed
Charlotte, NC
-
π§ - Skills detailed
#Data Engineering #dbt (data build tool) #Terraform #Data Pipeline #Programming #ML (Machine Learning) #S3 (Amazon Simple Storage Service) #SQL (Structured Query Language) #AI (Artificial Intelligence) #Snowflake #Storage #"ETL (Extract #Transform #Load)" #Data Management #AWS (Amazon Web Services) #Data Access #Infrastructure as Code (IaC) #Data Architecture #Cloud #Databricks #Lambda (AWS Lambda) #Python #Scala #Data Storage #MDM (Master Data Management)
Role description
Job Title: MDM Data Engineer
Location-Type: Remote - EST hours required
Start Date: ASAP
Duration: Contract-to-Hire, 3-6 months
Compensation Range: $50-60/hr W2
Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship
Job Description:
This role is responsible for designing and maintaining scalable, cloud-native data pipelines and integrations that centralize data across a large, fragmented enterprise system landscape in support of a Master Data Management mission.
Job Summary
β’ Build and maintain ETL/ELT pipelines to extract, transform, and load data from 20 enterprise systems into a central data architecture
β’ Develop, deploy, and optimize APIs to enable seamless data access for analytics, reporting, and operational systems
β’ Work within Microsoft Dynamics to understand system structure, pull data, and build integrations against it
β’ Create and define cost centers by standardizing attributes across all enterprise systems to establish a consistent data language across the organization
β’ Write Python code daily as the primary language for data engineering tasks across the team
β’ Leverage AWS services, primarily S3 for data storage and Lambda for event-driven functions, to support cloud-native workflows
β’ Incorporate AI tools into day-to-day engineering work and continuously identify process improvement opportunities
β’ Collaborate within a small, pod-based team structure alongside a tech lead, data engineer, BA, UX, and PM
Minimum Requirements:
β’ 3-10 years of overall experienceΒ in data engineering, data architecture, or a closely related role
β’ 3 years of hands-on Python programming experience
β’ 3 years of experience building and managing ETL/ELT data pipelines
β’ Proficiency with AWS services, specifically S3 and Lambda
β’ Strong SQL skills with the ability to write performant queries across various data stores
β’ Experience designing and integrating APIs into data workflows
β’ Resume profile reflecting a 70/30 split, data engineering background with some developer or application-building crossover
Preferred Qualifications:
β’ Experience with Snowflake or other modern data stack tools such as dbt or Databricks
β’ Familiarity with Microsoft Dynamics or similar enterprise platforms
β’ Background in MDM, sales data, or sales analytics environments
β’ Broader programming or application development experience, including having built an application end to end
β’ Familiarity with machine learning pipelines or AI-driven analytics workflows
β’ AWS certifications, such as AWS Solutions Architect
β’ Experience with Infrastructure as Code tools like Terraform or AWS CloudFormation
Job Title: MDM Data Engineer
Location-Type: Remote - EST hours required
Start Date: ASAP
Duration: Contract-to-Hire, 3-6 months
Compensation Range: $50-60/hr W2
Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship
Job Description:
This role is responsible for designing and maintaining scalable, cloud-native data pipelines and integrations that centralize data across a large, fragmented enterprise system landscape in support of a Master Data Management mission.
Job Summary
β’ Build and maintain ETL/ELT pipelines to extract, transform, and load data from 20 enterprise systems into a central data architecture
β’ Develop, deploy, and optimize APIs to enable seamless data access for analytics, reporting, and operational systems
β’ Work within Microsoft Dynamics to understand system structure, pull data, and build integrations against it
β’ Create and define cost centers by standardizing attributes across all enterprise systems to establish a consistent data language across the organization
β’ Write Python code daily as the primary language for data engineering tasks across the team
β’ Leverage AWS services, primarily S3 for data storage and Lambda for event-driven functions, to support cloud-native workflows
β’ Incorporate AI tools into day-to-day engineering work and continuously identify process improvement opportunities
β’ Collaborate within a small, pod-based team structure alongside a tech lead, data engineer, BA, UX, and PM
Minimum Requirements:
β’ 3-10 years of overall experienceΒ in data engineering, data architecture, or a closely related role
β’ 3 years of hands-on Python programming experience
β’ 3 years of experience building and managing ETL/ELT data pipelines
β’ Proficiency with AWS services, specifically S3 and Lambda
β’ Strong SQL skills with the ability to write performant queries across various data stores
β’ Experience designing and integrating APIs into data workflows
β’ Resume profile reflecting a 70/30 split, data engineering background with some developer or application-building crossover
Preferred Qualifications:
β’ Experience with Snowflake or other modern data stack tools such as dbt or Databricks
β’ Familiarity with Microsoft Dynamics or similar enterprise platforms
β’ Background in MDM, sales data, or sales analytics environments
β’ Broader programming or application development experience, including having built an application end to end
β’ Familiarity with machine learning pipelines or AI-driven analytics workflows
β’ AWS certifications, such as AWS Solutions Architect
β’ Experience with Infrastructure as Code tools like Terraform or AWS CloudFormation





