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Senior Data Engineer Category: Software Development/ Engineering
Main location: United States, Puerto Rico, Guaynabo
Position ID:J1126-0777
Employment Type: Full Time
Position Description: Join a collaborative, technically driven team as a Senior Databricks Data Engineer, where you will have the opportunity to take ownership of designing and delivering scalable, enterprise grade data integration solutions.
This role offers a unique opportunity for an experienced, hands on engineer to make a meaningful impact by driving end to end development of modern data pipelines using Databricks and Apache Spark. You will have the autonomy to influence technical decisions, solve complex engineering challenges, and contribute directly to the success of enterprise data initiatives.
You will work alongside experienced architects, engineers, and business stakeholders in an environment that values technical expertise, collaboration, innovation, and individual accountability. With flexibility across cloud technologies (AWS, Azure, or GCP), this position provides an excellent opportunity to leverage your existing expertise while expanding your technical capabilities and contributing to impactful data engineering solutions.
This position is located in Guaynabo, Puerto Rico in a hybrid working environment.
Your future duties and responsibilities: Data Engineering and Pipeline Development
• Design, develop, maintain, and enhance production grade ETL/ELT pipelines using Databricks, Apache Spark, Python/PySpark, and SQL.
• Develop scalable batch and incremental data integration pipelines across files, databases, and enterprise data sources.
• Build reusable, maintainable, and high performing data processing solutions that support business and operational requirements.
• Optimize Spark workloads to improve performance, scalability, reliability, and cost efficiency.
• Implement data quality, reconciliation, monitoring, validation, and error handling processes to ensure reliable data pipelines.
Solution Design and End to End Ownership
• Manage the complete data engineering lifecycle, including requirements analysis, solution design, development, testing, deployment, and production readiness.
• Prepare technical solution designs and participate in architecture and design reviews.
• Implement approved technical solutions in accordance with established architecture, engineering, security, and development standards.
• Analyze complex technical issues, identify root causes, and develop effective and sustainable solutions.
• Take ownership of assigned technical deliverables, ensuring solution quality, timely completion, and adherence to project commitments.
SQL, Data Modeling, and Analytics
• Develop and maintain complex SQL queries and data transformations, including data cleansing, enrichment, aggregation, and validation.
• Design and maintain curated datasets, data models, and reporting ready data structures to support analytical and operational needs.
• Collaborate with stakeholders to understand downstream data consumption, reporting, and analytics requirements.
• Ensure data structures and processing solutions support accuracy, consistency, scalability, and efficient downstream consumption.
Engineering Operations and Collaboration
• Develop and manage data pipeline orchestration using Databricks Workflows, Apache Airflow, or comparable technologies.
• Apply CI/CD, version control, automated testing, and deployment practices in accordance with established engineering standards.
• Monitor, troubleshoot, and resolve data pipeline failures, performance issues, data quality problems, and production incidents.
• Collaborate with architects, engineers, integration teams, business stakeholders, and other technical resources to design and implement effective data solutions.
• Document technical designs, implementation decisions, data processing methodologies, operational procedures, and support requirements.
• Identify opportunities to improve, standardize, and automate data engineering processes and solutions.
• Support production deployments, operational readiness activities, and ongoing maintenance and enhancement of data solutions.
Required qualifications to be successful in this role:• Experience implementing Databricks solutions in cloud environments such as AWS, Azure, or GCP, with no preference for a specific cloud provider.
• Experience with Delta Lake, Databricks Unity Catalog, and modern lakehouse architecture.
• Familiarity with dimensional data modeling, enterprise data warehousing, and analytical data architectures.
• Experience implementing automated testing, data quality controls, data observability, and advanced pipeline monitoring solutions.
• Familiarity with infrastructure as code tools and cloud native deployment practices.
• Experience contributing to enterprise scale data modernization, integration, or transformation initiatives.
• Experience with Spark performance tuning, workload optimization, and cloud cost optimization.
• Experience developing batch and incremental data processing solutions.
• Experience with data reconciliation, monitoring, observability, and production data quality management.
• Familiarity with fact and dimension modeling, curated data layers, and reporting ready data structures.
• Experience troubleshooting production data pipelines and supporting operational reliability.
• Experience preparing technical documentation and participating in technical design and architecture reviews.
• Strong analytical and problem solving skills, with the ability to work independently and manage assigned technical deliverables.
• Strong cross functional communication and collaboration skills, including experience working with technical and business stakeholders.
• Experience working in Agile delivery environments and participating effectively in iterative development and delivery processes.
Minimum Education Required:
• Bachelor's Degree
OPTIONAL: Desired qualifications/non-essential skills required
• Performance Optimization: Additional experience with advanced Apache Spark performance tuning, workload optimization, and cloud cost management.
• Data Architecture and Modeling: Familiarity with enterprise data warehousing, dimensional modeling (fact and dimension tables), and curated data layers.
• Data Quality and Observability: Exposure to advanced data quality frameworks, automated reconciliation, pipeline monitoring, and observability tools.
• Operational Excellence: Experience improving production pipeline reliability, troubleshooting complex performance issues, and implementing proactive monitoring solutions.
• Technical Design and Documentation: Experience contributing to architecture discussions, technical design reviews, and the development of engineering standards and documentation.
• Cross Functional Collaboration: Strong interpersonal and communication skills, with experience working across technical and business teams to deliver effective data solutions.
• Agile Delivery: Familiarity with Agile methodologies, iterative development practices, and collaborative engineering environments.
• Continuous Improvement: Proactive approach to identifying opportunities for automation, process optimization, and engineering efficiency.
• Knowledge Sharing: Willingness to mentor colleagues, share technical expertise, and contribute to a collaborative, team-oriented engineering culture.
CGI anticipates accepting applications for this position through November 27, 2026.
Other Information:
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $81,600.00 $160,700.00.
CGI's benefits are offered to eligible professionals on their first day of employment to include:
• Competitive compensation
• Comprehensive insurance options
• Individual Retirement Account (IRA) Bonus: CGI offers an annual IRA Bonus equal to the maximum annual matching contribution available under the continental U.S.'s 401(k) Plan
• CGI share purchase plan
• Paid time off for vacation, holidays, and sick time
• Paid parental leave
• Learning opportunities and tuition assistance
• Wellness and Well-being programs
Skills: - Airflow
- Amazon CloudFront
- Azure
- Databricks
