Location: Remote - Europe Remote | Full-time Compensation: $110K - $125K We are hiring on behalf of our client who is a premier infrastructure provider within the decentralized web (Web3) ecosystem, serving as the critical connectivity layer for tens of thousands of applications and millions of users globally. Having established a dominant market position, the organization is now expanding its horizons by launching a sophisticated payments solution. This new initiative enables merchants and payment providers to utilize blockchain rails for stablecoin checkouts, payouts, and deposits, already reaching millions of terminals worldwide through strategic global partnerships. The data systems supporting this infrastructure are foundational to the company's success. As the organization transitions from MVP pipelines to a scalable production architecture, there is a need for a Senior Data Engineer to join the team. This individual will help design and operate the data foundation behind a global payments network, ensuring that systems tracking wallet connections, transaction health, and financial reconciliations are as reliable as the payment flows themselves. This role sits at the intersection of data engineering and backend systems. The successful candidate will build event-driven pipelines, maintain real-time processing systems, and develop backend services that expose critical data to internal platforms and APIs. Key Responsibilities - Data Platform & Pipeline Engineering: Design and operate scalable, near real-time data pipelines for payment and platform data. Evolution of the current architecture from MVP status to a high-availability production environment is a primary focus. - Financial Data Modeling: Model and process complex transactional and ledger-style data to support financial reconciliation, merchant reporting, and settlement tracking. - Data Quality & Observability: Ensure the accuracy and freshness of data across critical workflows. This includes building robust monitoring and alerting systems that meet the stringent reliability standards of financial infrastructure. - Backend & API Development: Build and maintain backend services to expose data to internal platforms and downstream consumers, ensuring clean integration points for product and engineering teams. - Operational Ownership: Own systems end-to-end, from initial deployment to ongoing monitoring and reliability. This includes contributing to engineering standards and operational playbooks within a remote-first, asynchronous environment.

Location: Remote - Europe Remote | Full-time Compensation: $110K - $125K We are hiring on behalf of our client who is a premier infrastructure provider within the decentralized web (Web3) ecosystem, serving as the critical connectivity layer for tens of thousands of applications and millions of users globally. Having established a dominant market position, the organization is now expanding its horizons by launching a sophisticated payments solution. This new initiative enables merchants and payment providers to utilize blockchain rails for stablecoin checkouts, payouts, and deposits, already reaching millions of terminals worldwide through strategic global partnerships. The data systems supporting this infrastructure are foundational to the company's success. As the organization transitions from MVP pipelines to a scalable production architecture, there is a need for a Senior Data Engineer to join the team. This individual will help design and operate the data foundation behind a global payments network, ensuring that systems tracking wallet connections, transaction health, and financial reconciliations are as reliable as the payment flows themselves. This role sits at the intersection of data engineering and backend systems. The successful candidate will build event-driven pipelines, maintain real-time processing systems, and develop backend services that expose critical data to internal platforms and APIs. Key Responsibilities - Data Platform & Pipeline Engineering: Design and operate scalable, near real-time data pipelines for payment and platform data. Evolution of the current architecture from MVP status to a high-availability production environment is a primary focus. - Financial Data Modeling: Model and process complex transactional and ledger-style data to support financial reconciliation, merchant reporting, and settlement tracking. - Data Quality & Observability: Ensure the accuracy and freshness of data across critical workflows. This includes building robust monitoring and alerting systems that meet the stringent reliability standards of financial infrastructure. - Backend & API Development: Build and maintain backend services to expose data to internal platforms and downstream consumers, ensuring clean integration points for product and engineering teams. - Operational Ownership: Own systems end-to-end, from initial deployment to ongoing monitoring and reliability. This includes contributing to engineering standards and operational playbooks within a remote-first, asynchronous environment.

Title: GCP Data Engineer Location: Anywhere Job Description: Type: Contract Category: Data Industry: Retail Workplace Type: Remote Reference ID: JN -042026-106374 Description: Our client, a leader in their industry, has an excellent opportunity for a GCP Data Engineer to work on a 12+ month contract position working 100% remote (EST). Due to client requirement, applicants must be willing and able to work on a W2 basis. For our W2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Responsibilities: • Design, build, and operate scalable data platforms and data products within the Enterprise Data Warehouse (EDW). • Develop and maintain core data domains, curated datasets, and semantic layers for downstream analytics consumers. • Partner with engineering teams to implement architectural patterns, support platform modernization, and improve data reliability. • Provide hands-on technical leadership through collaboration, code reviews, and complex backend data engineering work. • Drive performance, cost optimization, scalability, and analytical accuracy across the EDW ecosystem. Experience Requirements: • 3+ years of experience in backend data engineering or analytics platform engineering. • Must have hands-on experience working within GCP environments. • Strong hands-on experience with cloud data warehouses, with BigQuery required. • Advanced SQL expertise and strong working knowledge of Python. • Proven experience designing enterprise-grade data models, including curated or ADS datasets. • Experience with CI/CD and orchestration tools such as Jenkins and Airflow. Preferred Skills: • Experience with universal or shared semantic modeling across multiple domains or products. • Strong understanding of performance tuning, resilience, scalability, and cost optimization in large data environments. • Ability to work across teams and influence architectural decisions without direct authority. • Exposure to Dataform and Vertex AI is a plus. Education Requirements: Bachelor's degree or equivalent work experience #LI-JS1 Recruitment Transparency Notice Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening and hiring process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (noreply@eliassen.com, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group’s use of these tools, including AI tools, as part of the application and hiring process. Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range. W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality. If anyone reaches out to you about an open position connected with Eliassen Group, please ensure that you are working directly with us by confirming the following: · When you work with Eliassen Group, all email communication will come from an Eliassen.com address, never Gmail, Yahoo, etc. · Eliassen Group will never ask you for personal information (home address, bank account, or check routing number) until you have worked with someone clearly associated with Eliassen Group. If you have any indication of fraudulent activity, please contact fraud@eliassen.com. About Eliassen Group: Eliassen Group is a strategic consulting firm that helps organizations reach further and achieve more through our technology, business advisory, and life sciences solutions. For nearly 40 years, we have combined exceptional people, deep domain expertise, and intelligent capabilities to expand our clients’ capacity and accelerate meaningful outcomes. We are driven by a purpose to positively impact the lives of our employees, clients, consultants, and the communities we serve. Eliassen is committed to building a diverse and inclusive team from a variety of backgrounds, perspectives, and skills. We are an Equal Opportunity and Affirmative Action Employer and all employment decisions are based on merit, performance, and business needs. Eliassen does not discriminate on the basis of race, color, gender identity or expression, sexual preference or orientation, sex (including pregnancy, childbirth, and related medical conditions), marital status, creed, religion, physical or mental disability, genetic information, military or veteran status, age, ancestry, national origin, citizenship status, prohibited criminal record inquiries of applicants and employees, or any other category protected by federal, state, or local laws. Don’t miss out on our referral program! If we hire a candidate that you refer us to then you can be eligible for a $1,000 referral check! Eliassen Group is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status. Eliassen Group’s Affirmative Action Plan (AAP) is available for inspection by any employee or applicant for employment upon request, during normal business hours of Monday through Friday, 8:30am to 5:30pm EST. Interested persons should contact Phaedra Wells at pwells@eliassen.com for assistance. It is unlawful in Massachusetts and Maryland to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

• Diseñar, construir y mantener pipelines de datos (ETL/ELT) • Integrar datos desde múltiples fuentes (APIs REST, PMS, archivos CSV, entre otros) • Construir y gestionar la capa de staging (datos crudos) utilizando SQL • Transformar, limpiar y modelar datos hacia una capa estructurada (data mart / modelo limpio) • Optimizar consultas y rendimiento en bases de datos • Trabajar con Redshift u otros data warehouses en AWS • Colaborar con el equipo de BI para asegurar que los datos sean consistentes, confiables y utilizables • Identificar oportunidades de mejora en la arquitectura de datos • Asegurar la calidad, integridad y fiabilidad de los datos