Lead Data Engineer: Build Scalable Pipelines & Lead Teams

PNC; Farmers Branch (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical Coverage

Prescription Drug Coverage

Dental Options

Vision Options

Life Insurance

Short-Term Disability Protection

Long-Term Disability Protection

401k

Pension

Stock Purchase Plans

Dependent Care Reimbursement

Child/Elder Care

Adoption Reimbursement

Educational Assistance

Wellness Program

Job summary

PNC is seeking a Senior Data Engineer to design, develop, and maintain scalable data pipelines and data platforms. You will collaborate with business stakeholders and provide technical leadership to junior engineers, ensuring robust data architectures and reliable delivery of analytics solutions.

The ideal candidate has a university degree and 3+ years of experience in data engineering, with hands-on expertise in ETL/ELT, Spark, SQL, and modern data tooling.

Qualifications

• University degree and 3+ years of experience in data engineering required.
• Preferred skills include application development, process improvements, and software solutions.

Responsibilities

• Design, develop, and maintain scalable data pipelines and frameworks.
• Collaborate with business stakeholders and provide technical leadership to junior engineers.

Skills

Data Pipeline Development

Spark

SQL

ETL

ELT

Containerization

Docker

Kubernetes

Object Storage

Data Lake

DevOps

CI/CD

Performance Optimization

Data Architecture

Collaboration

Leadership

Education

University degree

Bachelor's degree in data engineering or related field

Job description

PNC is seeking a Senior Data Engineer to design, develop, and maintain scalable data pipelines and data platforms. You will collaborate with business stakeholders and provide technical leadership to junior engineers, ensuring robust data architectures and reliable delivery of analytics solutions.

The ideal candidate has a university degree and 3+ years of experience in data engineering, with hands-on expertise in ETL/ELT, Spark, SQL, and modern data tooling.