Senior GCP Data Engineer

CVS is seeking an experienced Senior GCP Data Engineer for a contract-to-hire opportunity based in Hartford, Connecticut. This position requires a local candidate who can work onsite three days per week and collaborate effectively with both onshore and offshore teams. The successful candidate will bring at least seven years of hands-on experience with Google Cloud Platform data services and a strong background in designing, developing, and supporting scalable data pipelines. The engineer will also demonstrate practical experience using generative AI technologies such as GPT and Gemini to address business use cases. Relevant AI use cases must be clearly documented on the candidate’s resume and discussed during the interview process.

This role requires excellent communication, documentation, analytical, and collaboration capabilities. The selected professional must be comfortable working independently while also contributing within a fast-paced Agile delivery environment. Experience with SAFe methodology is preferred. A ROPES assessment is required as part of the evaluation process.

Key Responsibilities

• Design, implement, enhance, and support robust data pipelines using Google Cloud Platform services, including BigQuery, Cloud Storage, and Pub/Sub.
• Develop and manage reliable data workflows using Cloud Composer 3 and Apache Airflow for scheduling, orchestration, dependency management, monitoring, and operational support.
• Write clean, efficient, reusable, and scalable Python code by applying advanced programming techniques and established data engineering practices.
• Create complex SQL queries in BigQuery using common table expressions, window functions, and appropriate performance-tuning strategies.
• Design and maintain real-time data processing solutions using Apache Kafka to support timely and dependable data movement.
• Model and administer MongoDB databases, with particular attention to scalable schema design, data access patterns, reliability, and maintainability.
• Use Shell scripting and Linux system administration capabilities to automate activities and support the underlying data infrastructure.
• Perform data profiling and implement practical validation techniques to maintain data quality, consistency, completeness, and integrity.
• Develop and maintain API integration scripts that enable service automation and seamless data exchange between platforms.
• Investigate, troubleshoot, and resolve data pipeline, processing, integration, and data-quality issues through structured analysis and problem solving.
• Create and maintain clear data flow diagrams that communicate architecture, dependencies, transformations, and pipeline logic to technical and business stakeholders.
• Apply distributed-systems concepts and data engineering best practices when designing scalable, resilient, and supportable solutions.
• Use GPT and Gemini in practical business scenarios and demonstrate how generative AI has been incorporated into prior work or delivery processes.
• Participate in Agile ceremonies and delivery activities while supporting coordinated planning, execution, documentation, and continuous improvement.
• Collaborate with offshore delivery and support teams, ensuring effective handoffs, clear documentation, and timely resolution of technical issues.
• Contribute to development and automation activities involving GitHub, RTC, and related automation tools when applicable.

Required Qualifications

• Minimum of seven years of proven, hands-on experience working with GCP data services in production-oriented environments.
• At least three years of hands-on experience with BigQuery, Cloud Storage, Pub/Sub, Cloud Composer, Apache Airflow, Python, SQL, Apache Kafka, MongoDB, Shell scripting, Linux administration, data profiling, data validation, and API integration.
• Demonstrated experience creating advanced BigQuery SQL, including window functions, common table expressions, and query performance tuning.
• Strong understanding of distributed systems, scalable data architecture, workflow orchestration, and data engineering best practices.
• Demonstrable experience with GPT and Gemini, including clear business use cases documented on the resume.
• Strong analytical and troubleshooting abilities, with the capacity to resolve complex data-related issues effectively.
• Excellent written and verbal communication skills, including the ability to produce accurate technical documentation and architecture diagrams.
• Ability to work independently and collaboratively in a fast-paced environment with onshore and offshore stakeholders.
• Hands-on experience working in an Agile methodology. Experience with SAFe methodology is preferred.
• Candidate must be local to Hartford, Connecticut, and available to work onsite three days each week.
• Candidate must meet the stated work-authorization requirements. Green Card holders, United States citizens, and Green Card EAD holders may be considered, subject to formal verification.
• Candidate must complete the required ROPES assessment during the selection process.

Preferred Qualifications

• Google Cloud Professional Data Engineer certification.
• Experience using GitHub, RTC, and automation tools in a collaborative engineering environment.
• Prior experience operating within an onshore/offshore support model and coordinating work across distributed teams.
• Experience supporting data platforms through development, testing, deployment, production operations, and issue resolution.

Engagement Details

• This is a contract-to-hire position offering an hourly C2C rate of $85.
• The work arrangement is hybrid, with three required onsite days per week in Hartford, Connecticut.
• Applicants must be local to the Hartford area and able to comply consistently with the onsite schedule.
• Conversion to full-time employment will depend on performance, business needs, and successful completion of applicable client requirements.