Data Engineer: Build Scalable Data Pipelines & Analytics

Cognizant; Columbus (OH); On-site; USD 58,500 - 71,500; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays plus Paid Time Off

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

A leading IT services company is seeking a motivated Data Engineer to join their Data Engineering team in Columbus, OH. The ideal candidate will design, develop, and maintain robust data pipelines using Python, Spark, and SQL, while ensuring data quality and compliance. This role requires strong programming skills and an understanding of data architectures for effective collaboration with data scientists and analysts. Candidates should be passionate about building scalable data solutions and enabling advanced analytics across the organization.

Qualifications

• Exposure in Python and SQL required.
• Ability to design and maintain data pipelines.
• Experience with data lake and data warehouse architectures is a plus.

Responsibilities

• Design and develop data pipelines using Python, Spark, and SQL.
• Collaborate with data scientists and stakeholders.
• Implement data quality checks and maintain documentation.

Skills

Python

SQL

Problem-solving

Analytical skills

Communication skills

Collaboration

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Spark

Airflow

Snowflake

Docker

Kubernetes

Job description

A leading IT services company is seeking a motivated Data Engineer to join their Data Engineering team in Columbus, OH. The ideal candidate will design, develop, and maintain robust data pipelines using Python, Spark, and SQL, while ensuring data quality and compliance. This role requires strong programming skills and an understanding of data architectures for effective collaboration with data scientists and analysts. Candidates should be passionate about building scalable data solutions and enabling advanced analytics across the organization.