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 We have an opening for a Senior Data Engineer. The Senior Data Engineer is responsible for designing, building and maintaining modern data pipelines and data integration solutions in the Azure Cloud. This role enables enterprise analytics by delivering clean, timely and well-structured data to platforms such as Power BI. The Senior Data Engineer collaborates closely with architects, analysts and business stakeholders to deliver scalable, secure and efficient data solutions using Azure Data Factory, Azure Data Lake Storage (ADLS), Databricks, and Azure DevOps. In this capacity, the Senior Data Engineer will: - Design, build and manage scalable data pipelines using Azure Data Factory (ADF), Azure Data Lake Storage (ADLS) and Azure Databricks; - Develop ELT frameworks for ingesting and transforming structured and semi-structured data from on-prem and cloud sources; - Implement robust DevOps pipelines for code versioning, testing, deployment and monitoring using Azure DevOps; - Ensure pipeline performance, reliability and observability using tools like Azure Monitor and Log Analytics; - Collaborate with BI teams to support Power BI datasets and ensure optimal data model performance; - Automate environment setup, configuration and permissions using infrastructure-as-code where possible; - Write modular, testable code in Python or PySpark and manage version control with Git; - Support production operations, root cause analysis and performance tuning; - Maintain technical documentation for pipelines, data mappings and deployment processes; - Work as part of an Agile delivery team, participating in sprints, retrospectives and code review; - Mentor junior data engineers and promote best practices in CI/CD, version control, and release management. Qualifications - Bachelor’s degree in Computer Science, Engineering or related field (required); - 7+ years of data engineering or BI development experience; - 3+ years building data solutions in Microsoft Azure Cloud; - 2+ years using Azure DevOps for automated builds, releases and pipeline orchestration; - Proven experience working with structured and semi-structured data (Parquet, JSON, Avro); - Experience in professional services, legal, or financial environments preferred. Requirements - Advanced proficiency in Azure Data Factory, Azure Data Lake Storage (Gen2) and Azure Databricks; - Experience building and managing CI/CD pipelines in Azure DevOps for data solutions; - Strong SQL and ELT experience; familiarity with schema design (e.g., star, snowflake, denormalized); - Hands-on expertise with PySpark and Databricks notebooks, including Delta Lake workflows; - Familiarity with Git, branching strategies and repository management within Azure Repos; - Understanding of data security and privacy best practices in Azure (RBAC, managed identities, encryption); - Experience with Power BI dataflows, datasets and refresh configuration (preferred); - Familiarity with data cataloging and governance tools (e.g., Microsoft Purview) a plus; - Experience with Agile tools such as Azure Boards or JIRA. Benefits - Medical, Dental, Vision, Life/AD&D, Long Term Care, and Short- and Long-Term Disability; - Flexible Spending Accounts and Health Savings Account; - Healthcare Concierge and Advocacy; - Lifestyle Spending Account; - Voluntary 401(k) Plan and Profit Sharing; - 10 Paid Holidays per year and a generous PTO Program; - Family Support including Paid Parental Leave, Fertility Benefits, Breast Milk Shipping, Back-up Child Care, Elder Care, and Tutoring; - Wellbeing programs (Employee Assistance Program, Relationship Support, Mental Health, Menopause and Midlife Health and Well-Being Events); - Retirement Plan Consulting; - Anniversary Bonus Program; - Professional Development Programs; - Transportation and Commuter Benefits; - International Travel Insurance; - Critical Illness, Hospital Indemnity and Accident Insurance; - Auto/Home/Pet Insurance; - Prepaid Legal Insurance; - Employee Discounts; - And More!

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.