Spark Engineer

Job Description Our financial services client oversees within a large US bank with presence internationally the Data Pipelines and Automation Services within a Chief Data Office. The team our client is leading is responsible for enterprise data platform modernization initiatives spanning data movement automation platform engineering and operational transformation. The client is responsible for the bank for enterprise ETL platforms data pipeline frameworks and automation services that enable secure governed and scalable data delivery across hybrid cloud environments. The team is executing strategic modernization programs including legacy platform retirement cloud‑native platform adoption containerization CI/CD implementation and operational process automation. The team for this project is leading the development of a greenfield best‑of‑breed from scratch next‑generation enterprise data pipeline platform that unifies data engineering standards governance lineage and deployment across multiple data processing technologies and environments. The project team is building a platform to unify data pipeline execution across the enterprise and leading greenfield platform that requires for engineer roles on the team a strong understanding of APIs, Python, Sparkflow, Docket, K8s, Automated CI/CD with GitHub Actions or other tools, composable services, data governance and distributed systems. The goal is to turn complex systems into clean reusable services via Python. Role Overview Seeking a System Engineer US L4 to support a greenfield platform initiative with a focus on building integrations with Spark Engine and Spark Flow. This role requires strong expertise in system design and development, distributed computing and API integrations along with the ability to work independently with minimal guidance in a highly regulated enterprise environment. Key Responsibilities Design and develop scalable integrations with Spark Engine and Spark Flow for the Unity platform. Develop and consume RESTful APIs and services to enable seamless system interoperability. Work with large‑scale distributed compute frameworks to process and manage high‑volume data. Drive performance tuning, optimization and scalability improvements. Qualifications Experience with Apache Spark, Spark Engine, Spark Flow. Familiarity with big data ecosystems: Hadoop, Hive, SQL, Kafka. Exposure to cloud platforms: AWS, Azure or GCP. Hands‑on experience building and integrating APIs and microservices. Strong problem‑solving and debugging skills. Compensation The base compensation range for this role in the posted location is: $62,000 - $72,000. 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. Benefits Paid time off based on employee grade (A‑F), as 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. Additional Information 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 is an Equal Opportunity Employer encouraging diversity in the workplace. 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. 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. 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. #J-18808-Ljbffr Women Veterans Interactive