Role Description As a Senior Data Engineer, you will drive the end-to-end development of our core data infrastructure through AI-native engineering. Championing our AI DevEx approach, you will orchestrate AI agents to rapidly build, scale, and refactor high-performance systems. We are looking for a technical expert who takes hands-on ownership of distributed, real-time architectures. Leveraging your deep data engineering expertise, you will construct the robust pipelines that power our next-generation data products. - Developing and driving the architecture of complex data systems that prioritize scalability, reliability, and long-term maintainability. - Designing and optimizing production-grade data pipelines, with a primary focus on high-throughput, real-time streaming. - Driving Spec-Driven Development (SDD) using OpenSpec or GitHub Spec Kit to create strict engineering contracts that ensure predictable, high-quality AI code generation. - Orchestrating agentic AI workflows with Claude Code and the Model Context Protocol (MCP) to rapidly build, refactor, and scale our data infrastructure. - Taking full accountability and ownership of system components, working in a self-sufficient manner to solve deep technical challenges. - Implementing rigorous testing and monitoring frameworks to ensure the integrity of mission-critical data. - Mentoring junior engineers and fostering a culture of technical excellence through open feedback and architectural reviews. Qualifications - 10+ years of professional experience, with 5+ years specifically focused on Data Engineering. - Deep technical expertise with Kafka (including Producers, Consumers, and Stream Processing) for building scalable, real-time architectures. - Strong experience with OLAP databases (expertise in Clickhouse is highly preferred). - Good fluency in Python and SQL for complex data manipulation, optimization, and system building. - Willingness to embrace highly agentic AI-assisted development, specifically using Claude Code to autonomously navigate codebases, execute multi-step engineering tasks, and accelerate development cycles while maintaining high code quality. - Strong hands-on experience with Docker, Kubernetes, and automated CI/CD pipelines. - Significant experience with open-source tools and technologies within the modern data stack. - Excellent communication skills and a desire to work in an environment based on transparency and feedback. - Fluency in English. Benefits - Global & Diverse Team: Work in a collaborative, multicultural environment. - Flexibility: Flexible working hours to help you shape your own work-life balance. - Remote-First: A truly remote-friendly environment. - Growth: Ongoing career development, training, and coaching. - Learning Time: Six dedicated days per year for learning and development. - Culture: Regular team events (in-person and virtual) and location-based social benefits.

Role Description As a JUMO Junior Data Engineer, you will design, build and maintain scalable data architectures. You will monitor their performance, perform root cause analysis and provide solutions to any issues that might arise. You will work with large, complex data sets, which means experience working with Big Data is essential. On a typical day, we use Spark, Kafka, Python, SQL, Airflow and AWS technologies, such as Redshift. We work with Docker and Kubernetes for automating deployment, scaling, and management of containerized applications. - Be responsible for creating robust, mission critical batch and streaming data processing capabilities. - Design, implement, and maintain the data pipelines that constitute JUMO's data platform, enabling effective use of data across the organisation. - Provide feedback on team members' output, encouraging skills development within the team. - Work closely with Portfolio Managers and Decision Scientists to understand the real world problems we’re trying to solve. - Be supported by senior leaders as you drive your own development. Qualifications - BSc. in Computer Science, Electrical Engineering or equivalent tertiary degree. - Real-world understanding & experience of data pipeline design and development, as well as data processing and storage. - Experience in streaming technologies, specifically Spark and Kafka. - Experience with cloud technologies, AWS preferred. - Solid, proven experience working with big-data technologies such as Apache Spark, Flink, Hadoop, Kafka or Kinesis, DynamoDB. - Command of productionising and monitoring of data pipeline workflows, and working knowledge of the Data Product Lifecycle. - Experience in application design and development with at least one of the following languages: Python (preferred), Kotlin. - RDBMS experience in any relevant technology such as MySQL, PostgreSQL, Redshift and SQL Server. - Understanding of CI/CD practices. - Productive within a Linux command line environment. - Proven ability to contribute software as part of a team. Requirements - Experience working with messaging systems (RabbitMQ, Redis, SNS) - Bonus. - Experience working with data pipeline orchestration (Airflow, Nifi, Dagster) - Bonus. - Experience working with production BI environments and tools (Tableau, Superset, Looker) - Bonus. Benefits - Collaborating with smart, engaging people in an inspiring work environment. - Working for impact. - Growing and learning continuously, with loads of encouragement and support. - Boldly taking risks as we navigate new challenges. - Flexible work practices enabling your best delivery. - Being autonomous and empowered to lead. - A stack of leading-edge technologies. Company Description At JUMO, we’ve built a smart financial services platform to make finance accessible to everyone. We operate a remote first working approach, where working remotely is our default way of working. Our environment is designed to foster innovation and enable collaboration. - Diversity strengthens our teams. - We are dedicated to fostering an inclusive recruitment process that cultivates an environment where all individuals can be authentic, collaborate, and thrive.

• Definir, diseñar e implementar soluciones de datos end‑to‑end , participando en todo el ciclo del proyecto: desde el diseño de pipelines y modelado analítico hasta el seguimiento del delivery. • Diseñar y evolucionar arquitecturas modernas de datos basadas en Snowflake, dbt y Fivetran , asegurando buenas prácticas de rendimiento, seguridad y mantenimiento. • Liderar y coordinar el desarrollo de pipelines de datos y modelos analíticos , asegurando la calidad y alineación con las necesidades de negocio. • Actuar como interlocutor con el cliente , gestionando stakeholders, liderando workshops funcionales y sesiones de discovery, y acompañando durante toda la ejecución del proyecto. • Traducir requisitos de negocio en soluciones técnicas , aportando visión consultiva y criterio estratégico en la toma de decisiones. • Coordinar y dar soporte a equipos técnicos o pequeños squads , asegurando el avance correcto del trabajo y el cumplimiento de objetivos. • Impulsar la modernización y evolución de plataformas de datos , manteniendo una orientación clara a resultados y valor para el cliente.

Title: Associate Data Engineer Location: United States, Remote Department: Data Science Job Category: Data Science Requisition Number: ASSOC001075 Full-Time Remote Remote - General (United States) Job Description: Position summary Candid is a nonprofit that provides the most comprehensive data and insights about the social sector. We get you the information you need to do good. Candid currently has an opportunity for an Associate Data Engineer. The Associate Data Engineer supports the day-to-day operations of Candid’s cloud data platform. This role is responsible for maintaining ingestion and transformation pipelines built on Apache Iceberg, validating data outputs through schema and structural changes, and assisting with storage management, platform observability, and metadata operations. The Associate Data Engineer develops foundational skills across the modern data lakehouse stack while taking direct ownership of pipeline maintenance, documentation, and validation activities. Position: Associate Data Engineer Reporting to: Data Operations Manager Supervises: N/A Schedule: 35-hour work week, Monday through Friday Compensation: $70,000 - $95,000 (this range is for the NYC area and will be adjusted for other localities; additionally, factors like skills and experience will be considered). Location: Remote. In-person attendance is expected twice per year during our annual, weeklong all-staff summits. Additional in-person meeting participation is expected at least once per quarter for senior leaders and at least once per month for the executive team. Staff not located in the NYC area are expected to travel for these meetings. Benefits: Health insurance (medical, dental, vision), retirement contribution with additional option for a match, paid life insurance and AD&D, paid leave time (PTO, compassionate leave, volunteer, holiday, parental), short-term and long-term disability, pre-tax transit, flexible spending accounts, supplemental insurance, summer hours, and Public Service Loan Forgiveness (PSLF) program eligible employer. Responsibilities - Pipeline Maintenance, Documentation, & Validation: Serve as the primary owner of ingestion pipelines and transformation table adjustments. Ensure continued, reliable data delivery and apply routine changes as business and schema needs evolve. Validate transformation outputs against expected results after schema or structural changes, documenting findings and escalating anomalies to the appropriate teams. - Storage & Platform Support: Assist with scheduling compaction and cleanup jobs to maintain Iceberg table health and query performance. Support partition evolution and snapshot retention management to control storage growth. - Observability & Metadata: Assist in implementing and maintaining CloudWatch metrics, alarms, and dashboards to ensure pipeline visibility. Contribute to tracking and reporting on platform performance metrics. Help maintain AWS Glue metadata refresh and statistics jobs that support query planning and optimization within the data platform. - Schema Coordination: Assist with coordinating schema changes across ingestion and transformation layers to maintain consistency end to end. Collaborate with the Data Operations Engineer to communicate impacts and sequence changes safely. - Infrastructure & Security: Support and maintain RBAC and ABAC (least privilege, standardized roles, and consistent tagging). Participate in access reviews and audits, documenting changes and escalating risks as needed. Requirements - 1– 3 years of experience in data engineering, analytics engineering, or a closely related technical role; internships and relevant academic project work considered. - Solid SQL skills, including writing, reading, and debugging queries against relational or columnar data stores. - Familiarity with cloud data concepts: object storage (Amazon S3), columnar file formats (i.e. Parquet), data-interchange formats (JSON, XML), or open table formats (i.e. Apache Iceberg). - Experience with or exposure to distributed SQL query engines such as Trino or Starburst - Familiarity with AWS services such as S3 and Glue. - Exposure to Apache Airflow, SSIS or another workflow orchestration platform - Experience writing or maintaining data pipelines in Python. - Familiarity with on-prem relational data systems (i.e. Microsoft SQL Server). - Strong attention to detail, especially around data validation and output accuracy. - Strong analytical and problem-solving skills. - Excellent written and verbal communication skills; ability to document findings clearly for both technical and non-technical audiences. - Ability to work independently and collaboratively as part of a distributed team. - Willingness to perform other duties and special projects as needed/requested. - Sensitivity and respect for racial, gender, sexual orientation, and cultural differences. - Champions and represents Candid’s core values: We’re driven, direct, accessible, curious, and inclusive. About Candid Candid’s mission is to get you the information you need to do good. The world’s problems are only growing, and change can’t wait. Nonprofits are needed now more than ever, but all too often their work goes without adequate support. Candid makes it easier and faster for nonprofits and funders to connect in pursuit of solutions to change the world. Candid is where nonprofits find grants, donors find nonprofits that inspire them, and all can gain insights about the work being done for good. Candid is a qualifying nonprofit organization as defined by the Public Service Loan Forgiveness Program. As such, Candid employees may claim their employment time on their PSLF application. We offer a competitive salary and excellent benefits. Due to the high volume of applicants we typically receive, we regret that we can only contact candidates we would like to interview. Candid is an equal opportunity employer. Candid provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.