[Hiring] Resident Solution Architect @Capgemini

Role Description

As a Resident Solution Architect, you will serve as a trusted technical advisor and hands-on leader for enterprise data and analytics initiatives. You will partner with client stakeholders and delivery teams to design, optimize, and scale modern data platforms leveraging Databricks and cloud-native technologies. This role combines deep technical expertise with consulting and architecture leadership to drive successful business outcomes.

• Lead the design and implementation of scalable data engineering and analytics solutions on Databricks.
• Partner with client and delivery teams to define architecture standards, best practices, and technical roadmaps.
• Provide hands-on guidance for data platform development, optimization, and production deployments.
• Drive performance tuning, scalability improvements, and cost optimization across cloud and Databricks environments.
• Collaborate with engineering teams to establish CI/CD, DevOps, and MLOps best practices.
• Mentor technical teams on distributed computing, Spark architecture, and modern data platform design.
• Evaluate emerging Databricks and cloud capabilities and recommend adoption strategies that align with business goals.

Qualifications

• 7+ years of experience in data engineering, data platforms, and analytics.
• Completed Databricks Data Engineering Professional certification and required training curriculum.
• Proven experience delivering 6-8+ successful projects with significant hands-on Databricks development expertise.
• Strong experience with distributed computing using Apache Spark, including understanding of Spark runtime internals and performance optimization techniques.
• Experience designing and deploying solutions across cloud platforms, with deep expertise in AWS, Azure, or GCP and working knowledge of at least one additional cloud ecosystem.
• Familiarity with CI/CD pipelines, production deployment practices, and cloud-native development methodologies.
• Working knowledge of MLOps frameworks, machine learning lifecycle management, and model deployment processes.
• Current knowledge of Databricks products, platform capabilities, and best practices for scalability, reliability, and governance.

Requirements

• The base compensation range for this role in the posted location is: $73,150 - $174,000.
• Compensation may vary based on multiple factors including geographic location, education, qualifications, certifications, relevant experience, skills, seniority, performance, market considerations, and internal pay equity.
• In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions.

Benefits

• 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.