Resident Solution Architect (Databricks)

Capgemini Engineering; Atlanta (GA); On-site; USD 73,000 - 174,000; Full time

Job summary

Capgemini Engineering invites a seasoned Resident Solutions Architect to lead enterprise data and analytics initiatives, designing, implementing, and optimizing scalable data platforms on Databricks and cloud-native technologies. You will partner with client stakeholders and delivery teams to drive outcomes.

The role combines hands-on engineering with architecture leadership, including CI/CD, DevOps, and MLOps practices.

Qualifications

• 7+ years of experience in data engineering, data platforms, and analytics.
• Databricks Data Engineering Professional certification and training.
• Proven experience delivering 6-8+ projects with hands-on Databricks development.
• Strong experience with distributed computing using Apache Spark and performance optimization.
• Cloud design/deployment across AWS/Azure/GCP with multiple clouds.

Responsibilities

• Lead design/implementation of scalable data engineering and analytics solutions on Databricks.
• Define architecture standards, roadmaps, and best practices with client teams.
• Provide hands-on guidance for data platform development and deployments.
• Drive performance tuning, scalability, and cost optimization in cloud/Databricks environments.
• Mentor teams on distributed computing, Spark, and modern data platform design.

Skills

Databricks

Apache Spark

Cloud platforms

CI/CD pipelines

MLOps knowledge

Education

Databricks Certification

Tools

CI/CD tooling

Job description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

About the job you're considering

As a Resident Solutions 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.

Location

Remote

Your role

• 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.

Your skills and experience

• 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.

The base compensation range for this role in the posted location is: $73,150 - $174,000

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.

Important Notice

Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end‑to‑end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.