Data Engineer II — Hybrid, Cloud-Driven Analytics

McLane Company, Inc.; Temple (TX); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Day 1 Benefits

Paid time off day 1

Pet insurance

Maternity/paternity leave

Tuition reimbursement program

Discount programs

Job summary

McLane Company, Inc. is seeking a Data Engineer II for a hybrid role based near Temple, TX. You will design and maintain scalable data pipelines, ETL/ELT processes, and data models to support analytics and BI initiatives.

The role requires 3–5 years in data engineering, with strong SQL, Python, and cloud experience (Azure/GCP). You will collaborate with analysts and stakeholders, ensure data quality, and follow DataOps practices in a modern cloud environment.

Qualifications

• Bachelor's degree in CS, IS, Data Engineering, or a related field.
• 3-5 years of progressive experience in data engineering or related roles.
• Strong experience with SQL, Python, and modern data frameworks/tools.
• Experience with cloud data platforms (Azure and/or GCP).
• Experience with DataOps, CI/CD, and orchestration workflows.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Build and optimize data integrations from multiple sources, ensuring data quality and reliability.
• Develop and manage data models, warehouses, and data lakes for reporting and analytics.
• Implement best practices, automation, monitoring, testing, and performance optimization.
• Collaborate with analysts, data scientists, and stakeholders to deliver scalable data solutions.
• Tackling data issues while complying with governance and security standards.
• Document architectures and solutions to support maintainability.

Skills

SQL

Python

Data pipelines

ETL/ELT

Cloud platforms

CI/CD

Education

Bachelor's degree in CS/IS/Data Eng

Tools

Azure

GCP

CI/CD pipelines

Workflow orchestration

Job description

McLane Company, Inc. is seeking a Data Engineer II for a hybrid role based near Temple, TX. You will design and maintain scalable data pipelines, ETL/ELT processes, and data models to support analytics and BI initiatives.

The role requires 3–5 years in data engineering, with strong SQL, Python, and cloud experience (Azure/GCP). You will collaborate with analysts and stakeholders, ensure data quality, and follow DataOps practices in a modern cloud environment.