MDM Data Engineer

Location: Remote, working EST hours Duration: 6–12-month contract-to-hire Pay: $60+/hour Job Description Our global Fortune 500 client, with U.S. headquarters in Charlotte, NC, is a world class food service provider with a strong presence across the nation. Celebrating almost 30 years in North America, this employee-focused company has received honors for diversity and inclusion, innovation, health and wellness, and company culture. CRG has successfully placed over 220 employees within the last 7 years within this organization, known for its continuous growth opportunities, fantastic benefits package, innovative technology, flexible work environment, and collaborative culture. We are seeking a hands-on, collaborative Master Data Management (MDM) Data Engineer to join our data platform team. This role involves designing and implementing scalable, cloud-native data architectures and solutions across AWS. You’ll work closely with data engineers, developers, and business stakeholders to manage data pipelines from ingestion to modeling, while also building APIs to support analytics, reporting, and business intelligence. Responsibilities • Design, develop, and deploy scalable and secure data pipelines and cloud-native architectures (data lakes, warehouses, and streaming pipelines) on AWS. • Build and maintain ETL/ELT workflows using AWS Glue, Lambda, and Python to support a variety of data integration needs. • Develop, deploy, and optimize APIs to enable seamless data access for business intelligence, analytics, and operational systems. • Analyze, debug, and resolve data quality issues and pipeline failures to ensure data accuracy and reliability. • Collaborate across teams—including data science, analytics, and software engineering—to design and implement reusable data models. • Ensure efficient, scalable, and secure serverless operations through performance tuning and best practices in AWS environments. • Create and maintain documentation, architecture diagrams, and data flow maps for internal and external use. • Implement and manage data governance, security protocols, compliance standards, and privacy best practices. • Incorporate AI tools, such as ChatGPT, to streamline engineering tasks, documentation, and data exploration. • Lead integration efforts with third-party APIs and data sources to expand the organization’s data capabilities. • Establish and enforce architectural best practices, CI/CD pipelines, and Infrastructure as Code (IaC) in collaboration with DevOps teams. • Mentor team members, stay current with AWS innovations, and champion modern data practices across the organization. Qualifications • Bachelor’s degree in computer science, Information Systems, Analytics, or related field. • 5+ years of experience in data architecture, engineering, or similar roles. • 3+ years of hands-on programming experience with Python. • 3+ years of experience building and managing ETL/ELT data pipelines. • Strong SQL skills and ability to write performant queries across various data stores. • Proficient with AWS services: Lambda, Glue, S3, DynamoDB, Athena, Redshift, and Snowflake. • Solid understanding of OLTP, ODS, and dimensional modeling techniques. • Experience designing APIs and integrating with API-driven data workflows. • Strong knowledge of serverless architecture patterns and best practices. • Excellent problem-solving, analytical, and communication skills. • Experience in agile development environments with CI/CD workflows. • Ability to collaborate across engineering, data, and business teams. Preferred Skills • AWS Certifications (e.g., AWS Solutions Architect). • Experience with modern data stack tools such as dbt, Snowflake, Databricks. • Familiarity with machine learning pipelines and AI-driven analytics. • Experience with Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation. • Background in DevOps and automated deployment strategies for data workflows. • Experience integrating with ServiceNow application. Our technology stack centers around Python and AWS, leveraging services such as S3, PostgreSQL, DynamoDB, Athena, Snowflake, Redshift, Lambda, and Glue. Familiarity with modern data stack technologies, DevOps, and data security best practices is a strong advantage. Category Code: JN008