Google Cloud Platform (GCP) Data Engineer with hands-on experience with Google Cloud Platform (GCP) services, particularly BigQuery, and be proficient in DBT (Data Build Tool) for data transformation and modeling. This role requires strong SQL skills, a solid understanding of data warehousing concepts, and light proficiency in Python for scripting and automation.
Key Responsibilities:
• Design, build, and maintain scalable data pipelines on GCP, primarily using BigQuery.
• Develop and manage DBT models to transform raw data into clean, tested, and documented datasets.
• Write complex and optimized SQL queries for data extraction, transformation, and analysis.
• Implement and maintain data warehousing solutions, ensuring performance, scalability, and reliability.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions.
• Monitor and troubleshoot data pipeline performance and data quality issues.
• Automate data workflows and tasks using Python scripts where necessary.
• Ensure data governance, security, and compliance standards are met.
Required Qualifications:
• Bachelor's degree in Computer Science, Information Systems, or a related field.
• 4-5 years of experience in data engineering or a similar role.
• Strong expertise in SQL with the ability to write efficient, complex queries.
• Proficiency in DBT for data modeling and transformation
• Hands-on experience with BigQuery and other GCP data services.
• Solid understanding of data warehousing principles and best practices.
• Basic to intermediate skills in Python for scripting and automation.
• Familiarity with version control systems like Git.
• Excellent problem-solving and communication skills.
Job Description
Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.
Job Description - Grade Specific
The primary focus is to help organizations design, develop, and optimize their data infrastructure and systems. They help organizations enhance data processes, and leverage data effectively to drive business outcomes.
The base compensation range for this role in the posted location is $110,000 to $120,000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
