Senior Cloud Data Engineer — GCP & Big Data

Capgemini; Nashville (TN); On-site; USD 130,000 - 170,000; Full time

Benefits offered by this job

Paid time off

Medical, dental, and vision coverage

Retirement savings plans (e.g., 401(k)

Life and disability insurance

Employee assistance programs

Job summary

Capgemini is seeking a Senior Data Engineer with strong Google Cloud Platform expertise to design, develop, and optimize enterprise-scale data platforms and pipelines. The role requires hands-on coding and leadership to drive data engineering best practices across the organization.

The candidate will work on real-time processing, multi-cloud environments, and DevOps practices including CI/CD, IaC, and Git.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 8+ years of experience in data engineering, data warehousing, or big data technologies.
• Strong programming skills in: SQL, Python, Java and/or Scala.
• Hands-on experience with distributed data processing frameworks: Apache Spark, Apache Beam.
• Proven expertise with GCP services: BigQuery, Dataflow, Dataproc, Pub/Sub, Composer (Airflow), Terraform.
• Experience with DevOps practices including CI/CD pipelines, Git-based source control, and Infrastructure as Code (IaC).
• Strong understanding of data modeling, ETL/ELT frameworks, and cloud data architectures.

Responsibilities

• Design, develop, and optimize enterprise-scale data platforms and data processing pipelines.
• Lead best practices across the data engineering organization.
• Hands-on technical proficiency and leadership capabilities to drive initiatives across teams.

Skills

SQL

Python

Java/Scala

GCP DevOps

CI/CD

Git

Infrastructure as Code

Data modeling

Education

Bachelor's degree in Computer Science/Information Systems/Engineering

Tools

BigQuery

Dataflow

Dataproc

Pub/Sub

Composer (Airflow)

Terraform

Vertex AI

Job description

Capgemini is seeking a Senior Data Engineer with strong Google Cloud Platform expertise to design, develop, and optimize enterprise-scale data platforms and pipelines. The role requires hands-on coding and leadership to drive data engineering best practices across the organization.

The candidate will work on real-time processing, multi-cloud environments, and DevOps practices including CI/CD, IaC, and Git.