Senior Data Engineer

This is a fully remote position, open to applicants in Maryland.

📋 Description

• This role involves managing and organizing data to facilitate all business processes in order to meet corporate and departmental objectives.

• It entails identifying trends and effectively communicating them within the organization to ensure proper utilization of data.

• Key responsibilities include resolving data issues and collaborating with the data architect to develop, align, and maintain architectures in accordance with business requirements.

• Create data pipelines from various sources to target locations, including MES, ERP, PLM, SCADA/historian, and quality systems, to support the enterprise Digital Thread, which involves formatting, cleaning, and updating data as business needs evolve.

• Develop and uphold precise data structure and mapping documentation, including metadata that aligns with specific business requirements.

• Design and publish domain-oriented, reusable data products that align with a data mesh model, ensuring clear ownership, SLAs, and discoverability while standardizing data structure and types across ETL/ELT processes.

• Grasp the overarching goals, define appropriate scopes, and work in collaboration with the data architect, application engineers, integration specialists, business analysts, and other technical experts to ensure timely, effective, and secure delivery of content to authorized users.

• Oversee the full life cycle development of current ETL/ELT deployments, applying software engineering practices to data pipelines, including version control (Git), automated testing, code reviews, CI/CD, and Infrastructure-as-Code (e.g., Terraform, CloudFormation) to ensure consistent and auditable deployments across environments.

• Collaborate with manufacturing operations, quality, and supply chain teams to provide 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 datasets suitable for AI/ML applications, 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

• A Bachelor's degree in Computer Science, Software Engineering, or a related science or engineering discipline is mandatory.

• An advanced degree is preferred.

• A minimum of four years of experience in Data Modeling, Data Solution Development, and Data Integration is required.

• Prior experience in integrating data from manufacturing and operational systems (such as MES, ERP, PLM, SCADA/historian, LIMS, or QMS) is highly desirable.

• Significant experience with data science tools and technologies, particularly Python, SQL, and/or C# .NET is necessary.

• Proven experience in analyzing business requirements, planning, executing, and resolving complex problems is essential.

• Practical experience with the AWS data stack (including 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—specifically in building domain-oriented data products, utilizing a data catalog, and applying federated governance—is highly sought after.

• Familiarity with implementing data governance, lineage, and cataloging on AWS (such as AWS Glue Data Catalog, Lake Formation, and tools like Collibra, Alation, Atlan, or OpenMetadata) is highly preferred.

🏝️ Benefits

• 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.

• Discounts on home and auto insurance.

• Optional supplemental life insurance.