Senior Data Engineer

MESO SCALE DIAGNOSTICS, LLC.

Data Engineer managing and organizing data for corporate goals. Responsible for developing data pipelines and collaborating with technical experts on data management.

Posted 7/18/2026full-timeRemote • Maryland • 🇺🇸 United StatesSenior💰 $101,400 - $154,650 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Modeling, Data Solution Development, and Data Integration, with a strong focus on building and maintaining data pipelines and architectures that align with business requirements. Proficient in utilizing AWS data stack tools and implementing data governance practices to support enterprise analytics and operational efficiency.

Highest-signal resume keywords

Data ModelingData Solution DevelopmentAWS Data StackPythonData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IntegrationData Pipeline DevelopmentETL/ELT ProcessesData ArchitectureData Analysis

Soft Skills

Problem SolvingCollaborationCommunication

Tools & Technologies

AWS S3AWS GlueAWS EMRAWS RedshiftAWS Lambda

Certifications & Qualifications

AWS Certified Data EngineerAWS Certified Data Analytics

Industry Keywords

Digital ThreadData MeshManufacturing SystemsOperational SystemsData Governance

Tech Stack

Tools & technologies

Amazon RedshiftAWSERPETL.NETPythonSQLTerraform

About the role

Key responsibilities & impact

This position is responsible for managing and organizing data to support all business processes to achieve corporate and departmental goals
This position is responsible for identifying trends and communicating these trends clearly to others in the organization to ensure data is properly used
Core activities include troubleshooting data issues, and assisting the data architect to develop, align, and maintain architectures with business requirements
Develop data pipelines from various data sources to target locations — including MES, ERP, PLM, SCADA/historian, and quality systems — to support the enterprise Digital Thread, including formatting, cleaning, and updating data as the business needs
Develop and maintain accurate data structure and mapping documentation, including metadata aligned to specific business requirements
Design and publish domain-oriented, reusable data products aligned to a data mesh model with clear ownership, SLAs, and discoverability — standardizing data structure and types across ETL/ELT processes
Understand the big picture, set the right scope, and collaborate with the data architect, application engineers, integration specialists, business analysts, and other technical experts to ensure adequate content delivery to authorized users in a timely, effective, and secure manner
Manage the full life cycle development for the current ETL/ELT deployments, applying software-engineering practices to data pipelines — version control (Git), automated testing, code review, CI/CD, and Infrastructure-as-Code (e.g., Terraform, CloudFormation) — to ensure repeatable, auditable deployments across environments
Partner with manufacturing operations, quality, and supply chain teams to deliver analytics on OEE, yield, scrap, throughput, engineering-change cycle time, time-to-release, and end-to-end product genealogy/traceability supported by the Digital Thread
Prepare AI/ML-ready datasets — including feature pipelines, dataset versioning, and curated knowledge sources for predictive quality, anomaly detection, and retrieval-augmented (RAG) use cases — in partnership with data science and AI teams

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, or other related science or engineering discipline is required
Advanced degree preferred
A minimum of four years experience in Data Modeling, Data Solution Development, and Data Integration
Experience integrating data from manufacturing and operational systems (MES, ERP, PLM, SCADA/historian, LIMS, or QMS) is highly preferred
Extensive experience working with data science tools/technologies, particularly Python, SQL, and/or C# .NET
Experience analyzing business requirements, planning, executing actions, and solving complex problems
Hands-on experience with the AWS data stack (S3, Glue, EMR, Redshift, Lake Formation, Kinesis, Lambda, and IAM) for building, securing, and operating production data platforms is required; AWS Certified Data Engineer or AWS Certified Data Analytics certification is highly preferred
Experience contributing to a data mesh, data fabric, or Digital Thread initiative — including building domain-oriented data products, using a data catalog, and applying federated governance — is highly preferred
Experience implementing data governance, lineage, and cataloging on AWS (e.g., AWS Glue Data Catalog, Lake Formation, and tools such as Collibra, Alation, Atlan, or OpenMetadata) is highly preferred

Benefits

Comp & perks

medical, dental, and vision coverage
prescription benefits
401(k) plan with company matching
flexible spending accounts
company-paid short- and long-term disability insurance
group life and accidental death and dismemberment insurance
paid vacation
paid sick leave
paid holidays
paid parental leave
employee assistance program
fitness club membership contribution
pet insurance
identity theft protection
home and auto insurance discounts
optional supplemental life insurance