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Bigquery Engineer

  • Bigquery Engineer job type Posted on: Oct 12, 2026
  • Bigquery Engineer experience level Openkyber
  • Bigquery Engineer employment type Atlanta, Georgia
  • Bigquery Engineer employment type Onsite
  • Bigquery Engineer salary Full-time

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Job Title :

Bigquery Engineer

Job Type :

Full-Time

Job Location :

Atlanta Georgia United States

Remote :

No

Jobcon Logo Job Description :

Lead Google Cloud Platform Data Engineer Hybrid (Madison, WI) Long-Term Contract

About the Role

We are seeking an experienced Lead Data Engineer to join a high-impact data and analytics team supporting initiatives across AI, Sales, Marketing, and Customer Analytics. This is a hands-on technical leadership role where you will design, build, and optimize scalable cloud-based data solutions while mentoring fellow engineers and driving engineering best practices. This position is approximately 70-75% hands-on development and 25-30% technical leadership/mentoring .

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL workflows.
  • Build and optimize data warehouse solutions and cloud-based data platforms.
  • Lead technical design discussions and promote best practices across engineering teams.
  • Mentor junior and mid-level engineers on architecture, coding standards, and performance optimization.
  • Ensure data quality, security, privacy, governance, and integrity throughout the data lifecycle.
  • Collaborate with business stakeholders to translate requirements into data solutions.
  • Develop reusable frameworks, libraries, and automation capabilities.
  • Support distributed data processing and large-scale analytics workloads.
  • Create and maintain documentation for critical processes and operational support.

Required Qualifications

  • 8+ years of experience in Data Engineering, Data Warehousing, or Big Data Engineering.
  • Expert-level experience with Google Cloud Platform (Google Cloud Platform) .
  • Strong hands-on expertise in Python development for data processing and ETL frameworks.
  • Advanced SQL skills with extensive experience in relational and analytical databases.
  • Experience building scalable data pipelines and cloud-native data solutions.
  • Strong knowledge of Spark , Hadoop, or other distributed data processing technologies.
  • Experience with data modeling, dimensional modeling, and star schema design.
  • Understanding of database internals, indexing, transactions, and query optimization.
  • Experience with REST APIs and web services.
  • Strong communication skills and ability to work directly with business stakeholders.

Preferred Qualifications

  • Experience with Machine Learning Engineering or ML-enabled data platforms.
  • Exposure to tools such as scikit-learn, Spark ML, H2O , or similar ML frameworks.
  • Experience with Infrastructure as Code (Terraform, Docker, CloudFormation, etc.).
  • Experience with CI/CD and DevOps tools including Jenkins and Git.
  • Background within insurance, financial services, or other data-driven industries.

Ideal Candidate

  • Strong Google Cloud Platform, Python, and SQL expertise.
  • Proven experience designing enterprise-scale data platforms.
  • Comfortable mentoring engineers and influencing technical direction.
  • Able to bridge business requirements with technical solutions.
  • Passionate about modern data engineering, analytics, and cloud technologies.

Recommended Dice Filters Must Have Skills: Google Cloud Platform, Python, SQL Nice to Have: Spark, BigQuery, Terraform, Machine Learning Experience Level: 8+ Years Employment Type: Contract Location: Wisconsin (Hybrid)

For applications and inquiries,

Jobcon Logo Position Details

Posted:

Oct 12, 2026

Reference Number:

106591-38381

Employment:

Full-time

City:

Atlanta

Job Origin:

CIEPAL_ORGANIC_FEED

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Lead Google Cloud Platform Data Engineer Hybrid (Madison, WI) Long-Term Contract

About the Role

We are seeking an experienced Lead Data Engineer to join a high-impact data and analytics team supporting initiatives across AI, Sales, Marketing, and Customer Analytics. This is a hands-on technical leadership role where you will design, build, and optimize scalable cloud-based data solutions while mentoring fellow engineers and driving engineering best practices. This position is approximately 70-75% hands-on development and 25-30% technical leadership/mentoring .

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL workflows.
  • Build and optimize data warehouse solutions and cloud-based data platforms.
  • Lead technical design discussions and promote best practices across engineering teams.
  • Mentor junior and mid-level engineers on architecture, coding standards, and performance optimization.
  • Ensure data quality, security, privacy, governance, and integrity throughout the data lifecycle.
  • Collaborate with business stakeholders to translate requirements into data solutions.
  • Develop reusable frameworks, libraries, and automation capabilities.
  • Support distributed data processing and large-scale analytics workloads.
  • Create and maintain documentation for critical processes and operational support.

Required Qualifications

  • 8+ years of experience in Data Engineering, Data Warehousing, or Big Data Engineering.
  • Expert-level experience with Google Cloud Platform (Google Cloud Platform) .
  • Strong hands-on expertise in Python development for data processing and ETL frameworks.
  • Advanced SQL skills with extensive experience in relational and analytical databases.
  • Experience building scalable data pipelines and cloud-native data solutions.
  • Strong knowledge of Spark , Hadoop, or other distributed data processing technologies.
  • Experience with data modeling, dimensional modeling, and star schema design.
  • Understanding of database internals, indexing, transactions, and query optimization.
  • Experience with REST APIs and web services.
  • Strong communication skills and ability to work directly with business stakeholders.

Preferred Qualifications

  • Experience with Machine Learning Engineering or ML-enabled data platforms.
  • Exposure to tools such as scikit-learn, Spark ML, H2O , or similar ML frameworks.
  • Experience with Infrastructure as Code (Terraform, Docker, CloudFormation, etc.).
  • Experience with CI/CD and DevOps tools including Jenkins and Git.
  • Background within insurance, financial services, or other data-driven industries.

Ideal Candidate

  • Strong Google Cloud Platform, Python, and SQL expertise.
  • Proven experience designing enterprise-scale data platforms.
  • Comfortable mentoring engineers and influencing technical direction.
  • Able to bridge business requirements with technical solutions.
  • Passionate about modern data engineering, analytics, and cloud technologies.

Recommended Dice Filters Must Have Skills: Google Cloud Platform, Python, SQL Nice to Have: Spark, BigQuery, Terraform, Machine Learning Experience Level: 8+ Years Employment Type: Contract Location: Wisconsin (Hybrid)

For applications and inquiries,

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