Senior Data Engineer: Data Pipelines & AI-Ready Analytics

Talentify; Maryland; Hybrid; USD 101,000 - 155,000; Full time

Job summary

Talentify is seeking an experienced data engineer to manage and organize data supporting enterprise processes. You will identify trends, troubleshoot data issues, and collaborate with architects and engineers to ensure compliant, high-quality data with scalable pipelines.

Responsibilities include building ETL/ELT deployments, delivering analytics on OEE and throughput, and preparing AI/ML-ready datasets in partnership with data science teams. Hybrid work model offered.

Qualifications

• Bachelor’s degree required in CS/SE or related field; advanced degree preferred.
• Minimum four years of experience in data modeling, data solution development, and data integration.
• Experience integrating data from MES, ERP, PLM, SCADA/historian, LIMS, or QMS systems preferred.
• Strong experience with Python, SQL, and/or C#/.NET for data processing.

Responsibilities

• Develop data pipelines from multiple sources to target locations (MES, ERP, PLM, SCADA) for the Digital Thread.
• Maintain accurate data structures and metadata aligned to business requirements.
• Design reusable data products with clear ownership, SLAs, and discoverability.
• Collaborate with data architects, engineers, analysts to ensure timely, secure data delivery.
• Manage full lifecycle of ETL/ELT deployments with Git, testing, CI/CD, and IaC.
• Partner with operations to deliver analytics on OEE, yield, scrap, throughput, and traceability.

Skills

Data modeling

Data integration

Python

SQL

C#/.NET

ETL/ELT design

Data governance

Communication

Education

Bachelor’s degree in Computer Science, Software Engineering, or related field

Tools

SSIS

Informatica

Talend

dbt

Fivetran

Airflow

Git-based workflows

Terraform

CloudFormation

Job description

Talentify is seeking an experienced data engineer to manage and organize data supporting enterprise processes. You will identify trends, troubleshoot data issues, and collaborate with architects and engineers to ensure compliant, high-quality data with scalable pipelines.

Responsibilities include building ETL/ELT deployments, delivering analytics on OEE and throughput, and preparing AI/ML-ready datasets in partnership with data science teams. Hybrid work model offered.