Data Engineer Google Cloud Platform Big Query Specialist

Position: Data Engineer Google Cloud Platform Big Query Specialist

Location: Miami/Tampa, FL /Irving, TX/New Jersey/Ashburn, VA

Terms: Fulltime

Job Summary:

The Data Engineer Google Cloud Platform BigQuery Specialist will be responsible for designing and implementing efficient data pipelines that extract, transform, and load (ETL) data from various relational databases into Google Cloud BigQuery. The ideal candidate should have strong SQL optimization skills to ensure fast and efficient data processing and movement. They must be comfortable working in a multi-vendor, dynamic work environment and collaborating with cross-functional teams. Key

Required Qualifications

• Bachelor s or Master s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 5+ years of experience in data engineering, ETL pipeline development, and SQL optimization.
• 3+ years of experience with Google Cloud Platform (Google Cloud Platform), specifically BigQuery.

Technical Skills:

• Expertise in SQL optimization for BigQuery and relational databases.
• Proficiency in ETL/ELT development using Cloud Composer (Apache Airflow), Dataflow (Apache Beam), and BigQuery Transfer Service.
• Experience with Python, Shell scripting, or Java for automation and data transformation.
• Strong knowledge of data partitioning, clustering, and materialized views in BigQuery.
• Familiarity with data orchestration tools like Apache Airflow, Cloud Composer, or dbt (Data Build Tool).
• Hands-on experience with Google Cloud Platform services such as Cloud Storage, Pub/Sub, Cloud Functions, and IAM.
• Understanding of data warehouse design, star schema modeling, and data normalization/denormalization.
• Experience with data quality frameworks and best practices for data validation and monitoring. Working knowledge of version control tools like GitHub, Bitbucket, or GitLab

Soft Skills:

• Strong problem-solving skills and the ability to troubleshoot performance issues.
• Ability to work in a fast-paced, dynamic, and multi-vendor work environment.
• Excellent communication skills to work effectively with stakeholders across teams.
• Ability to multitask and manage multiple projects simultaneously.

Preferred Qualifications (Must Have)

• Google Cloud Platform Professional Data Engineer Certification or BigQuery-related certifications.
• Experience with NoSQL databases (Bigtable, MongoDB, etc.).
• Knowledge of data streaming technologies (Kafka, Apache Flink, or Google Cloud Pub/Sub)

Preferred Qualifications (Nice to Have)

• Experience with BI Tools (Looker, Tableau, Power BI, or Google Data Studio).
• Familiarity with machine learning pipelines using BigQuery ML or Vertex AI

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Position: Data Engineer Google Cloud Platform Big Query Specialist

Location: Miami/Tampa, FL /Irving, TX/New Jersey/Ashburn, VA

Terms: Fulltime

Job Summary:

The Data Engineer Google Cloud Platform BigQuery Specialist will be responsible for designing and implementing efficient data pipelines that extract, transform, and load (ETL) data from various relational databases into Google Cloud BigQuery. The ideal candidate should have strong SQL optimization skills to ensure fast and efficient data processing and movement. They must be comfortable working in a multi-vendor, dynamic work environment and collaborating with cross-functional teams. Key

Required Qualifications

• Bachelor s or Master s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 5+ years of experience in data engineering, ETL pipeline development, and SQL optimization.
• 3+ years of experience with Google Cloud Platform (Google Cloud Platform), specifically BigQuery.

Technical Skills:

• Expertise in SQL optimization for BigQuery and relational databases.
• Proficiency in ETL/ELT development using Cloud Composer (Apache Airflow), Dataflow (Apache Beam), and BigQuery Transfer Service.
• Experience with Python, Shell scripting, or Java for automation and data transformation.
• Strong knowledge of data partitioning, clustering, and materialized views in BigQuery.
• Familiarity with data orchestration tools like Apache Airflow, Cloud Composer, or dbt (Data Build Tool).
• Hands-on experience with Google Cloud Platform services such as Cloud Storage, Pub/Sub, Cloud Functions, and IAM.
• Understanding of data warehouse design, star schema modeling, and data normalization/denormalization.
• Experience with data quality frameworks and best practices for data validation and monitoring. Working knowledge of version control tools like GitHub, Bitbucket, or GitLab

Soft Skills:

• Strong problem-solving skills and the ability to troubleshoot performance issues.
• Ability to work in a fast-paced, dynamic, and multi-vendor work environment.
• Excellent communication skills to work effectively with stakeholders across teams.
• Ability to multitask and manage multiple projects simultaneously.

Preferred Qualifications (Must Have)

• Google Cloud Platform Professional Data Engineer Certification or BigQuery-related certifications.
• Experience with NoSQL databases (Bigtable, MongoDB, etc.).
• Knowledge of data streaming technologies (Kafka, Apache Flink, or Google Cloud Pub/Sub)

Preferred Qualifications (Nice to Have)

• Experience with BI Tools (Looker, Tableau, Power BI, or Google Data Studio).
• Familiarity with machine learning pipelines using BigQuery ML or Vertex AI

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.