• Collaborate with product managers, data scientists, engineering, and program management teams to define product features, business deliverables and strategies for data products. • Collaborate with business partners, operations, senior management, etc. on day-to-day operational support. • Support operational reporting, self-service data engineering efforts, production data pipelines, and business intelligence suite. • Interface with multiple diverse stakeholders and gather/understand business requirements, assess feasibility and impact, and deliver on time with high quality. • Design appropriate solutions and recommend alternative approaches when necessary. • Work with high volumes of data, fine tuning database queries and able to solve complex technical problems. • Contribute to multiple projects/demands simultaneously. • Work in a fast paced, collaborative, and iterative environment. • Exercise independent judgment in methods and techniques for obtaining results. • Work in an agile/scrum environment. • Use state of the art technologies to acquire, ingest and transform big datasets.

Role Description Splash Financial is seeking a highly skilled and experienced Principal Data Engineer to design and implement a scalable, reliable, and high-performance data platform. In this role, you will be responsible for developing data models, architecting robust big data systems, and ensuring scalability and fault tolerance across our data ecosystem. What You’ll Do at Splash - Design and implement end-to-end big data solutions that meet functional and non-functional requirements, focusing on scalability, reliability, and performance. - Design logical and physical data models for structured, semi-structured, and unstructured data. - Work closely with engineering, data science, product, and infrastructure teams to ensure seamless data flow and system interoperability. - Optimize storage and processing layers for performance and cost-efficiency. - Ensure high availability and disaster recovery for the data platform. - Establish data governance standards including data quality, metadata management, and lineage tracking. - Conduct performance tuning and capacity planning for large-scale data environments. - Evaluate and recommend tools, frameworks, and technologies to enhance the data ecosystem. - Mentor junior data engineers and provide architectural guidance to cross-functional teams. Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field. - 10+ years of experience in big data architecture and data engineering roles. - Strong proficiency with big data technologies: Hadoop, Spark, Kafka, Hive, Presto, Flink, etc. - Expertise in data modeling, warehousing solutions (e.g. Snowflake, Databricks, BigQuery), and distributed systems. - Hands-on experience with cloud platforms (AWS preferred) and infrastructure-as-code (Terraform). - Knowledge of data privacy and financial data compliance regulations. - Excellent problem-solving and communication skills. - Experience in the lending/credit or broader financial services industry. - Experience using Fivetran, Dbt, Airflow and Snowflake. - Familiarity with MLOps tools (MLflow, Kubeflow) and real-time analytics. Requirements - Strong background in data engineering, distributed systems, and cloud infrastructure. - Deep understanding of best practices in data modeling, system architecture, and data governance. Benefits - Fully remote work freedom. - Competitive salary packages. - Flexible PTO + 9 company holidays. - Equity: Share in our start-up success. - Comprehensive and affordable insurance benefits. - Paid parental leave for both caregivers. - Essential equipment to get the job done. - 401(k) for your future savings. - Quarterly meet-ups: In person & virtual fun. - Awesome Splash swag to flaunt your team spirit.

Role Description Are you ready to tackle sophisticated distributed systems challenges at scale? Our Telemetry Platform team is looking for a Senior Software Engineer to help us build and evolve the services that collect and process data from millions of NVIDIA users worldwide. If you love working on high-impact infrastructure, we want to hear from you! - Build real-time, high-load data collection services; - Drive architectural decisions for shared infrastructure components: metrics, distributed tracing, and configuration management; - Collaborate with multi-functional teams on integration points and API contracts; - Ensure operational perfection: monitoring, and performance optimization. Qualifications - A Bachelor’s or Master's degree in Computer Science, Engineering, or a related field; - 5+ years of software engineering experience; - Proven Java expertise (Java 17+), including JMM and concurrency; - Proficiency in Spring Boot and reactive architecture (Project Reactor or similar); - Strong understanding of distributed systems, microservices architecture, and event-driven development; - Hands-on experience with Kubernetes, Docker, and message brokers (Apache Kafka preferred); - Proficient in English. Requirements - Experience with AWS Cloud technology stack (or similar); - Familiarity with observability tools, including Prometheus, Grafana, and distributed tracing (OpenTelemetry or similar); - Experience building and maintaining CI/CD pipelines (GitLab CI, Jenkins, or equivalent); - Knowledge of time-series or columnar databases (ClickHouse, Cassandra). Benefits NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. - Widely considered to be one of the technology world’s most desirable employers; - Offers highly competitive salaries; - Comprehensive benefits package. As you plan your future, see what we can offer to you and your family: www.nvidiabenefits.com

• Design, build, and maintain scalable, optimized data pipelines that support business intelligence and analytics use cases. • Partner with Enterprise, Solution, Technical Architecture, and Infrastructure teams to evolve data platform architecture. • Perform conceptual and logical data modeling to assemble data sets of varying size and complexity. • Develop and manage ETL/ELT processes using AWS and SQL-based technologies. • Implement analytical solutions that generate actionable insights into operational efficiency, donor acquisition, and key business metrics. • Collaborate with data, product, design, and executive stakeholders to support data needs and resolve technical issues. • Serve as a technical lead for Data Engineer I and II teammates by coaching, mentoring, and reinforcing best practices. • Conduct testing and root cause analysis to troubleshoot data quality, performance, and integration issues. • Provide structured and ad‑hoc knowledge sharing and documentation across teams. • Support data access configuration, integrations, and onboarding standards. • Partner with governance and security teams to enable data cataloging, lineage, and discovery.