Role Description As an Intermediate Data Engineer on our Data team, you'll be closely collaborating with engineering teams, designers, and stakeholders across the company to solve data problems that span the full stack — from pipelines and infrastructure to customer-facing data products. You'll be part of a small, dynamic team — the problems you'll work on won't always come with a neat brief, and we need someone who takes ownership and runs with it. Reporting to a Principal Data Engineer, your work will directly impact both internal decision-making and customer success. Your goal will be to help shape our data products and infrastructure to have a top-line impact on our company goals. Here's how you'll accomplish this: - Take ownership of undefined problems — dig in, scope the work, and ship solutions, whether that's a pipeline, a dashboard, a tracking implementation, or something we haven't thought of yet. - Ship customer-facing analytics dashboards and features — this is production code, not just SQL and charts. - Work directly with engineering teams to implement tracking services across our products. - Interface with teams across the company who need data solutions, translating fuzzy requirements into concrete deliverables. - Raise the bar on technical quality across the data team — through architecture decisions, reducing tech debt, code reviews, and bringing software development best practices to a high-performing data team. - Work with your team to conduct new technology research; bring fresh ideas and concepts to bear on how we integrate AI into our data workflows. Qualifications - 3–5 years of experience working across data engineering, full-stack development, analytics, or some combination. - Solid data engineering experience — you've built and maintained pipelines, worked with warehouses, and understand data modeling and quality. - Full-stack development experience — you've shipped production code that users interact with, not just internal tooling. - Hands-on experience with dbt and BigQuery or similar stacks (Snowflake, Databricks, etc.). - Self-motivated and resourceful — you ship things, communicate clearly across technical and non-technical teams, and are always looking to level up. - Comfortable working across the stack and across disciplines; you don't need to be an expert everywhere, but you're not afraid to jump in. - Loves to learn and grow — they’ve found (and keep looking for) ways to level up their skills in this field. Requirements - Experience with LLM/agent development — building AI-powered data products, automated workflows, or integrating LLMs into data pipelines and analytics. - Experience with GCP and Terraform. - Any exposure to ML. - Experience white-labeling a BI tool or embedding analytics into a customer-facing product. - Experience building or maintaining event tracking systems. - Familiarity with modern data stack tools beyond dbt/BigQuery (Airflow, Dagster, etc.). - Experience working in startup-style environments or autonomous teams within larger orgs. - Experience working in a SaaS environment. Benefits - Competitive compensation package including base salary, equity, team-wide bonuses, and an Employee Share Purchase Plan. - Flexible Paid Time Off to maintain mental and physical health — minimum 4 weeks of vacation, plus Thinker Holidays and time off for the December holiday season. - Comprehensive health benefits starting on Day 1, including health, vision, and dental coverage for you and your family, $3,000 for mental health care, and additional health spending accounts. - Generous parental leave top-ups for up to 32 weeks, fertility coverage, and personalized return to work options. - 3 Paid Volunteer Days each year to give back to your community. - Flexible Work — choose to work from home, at our Vancouver HQ, or anywhere with wifi. - An annual $2,000 CAD Learn and Grow fund for conferences, seminars, or courses, plus training, mentorship, coaching, and internal promotion opportunities. - A home office setup with a company-owned Macbook Pro and budget for ergonomic accessories. - A welcoming environment where you can bring your whole self to work.

• Own and maintain the data platform product backlog, ensuring it is well-prioritized, visible, and aligned with both technical and business objectives. • Co-author epics, features, and user stories with Data Engineers, including clear acceptance criteria, data contracts, and technical specifications. • Facilitate sprint planning, backlog grooming, and retrospectives in partnership with the Data Engineering team lead. • Actively triage incoming requests from Product Management, Data Analysts, Solutions Architecture, and Implementation/Support, translating them into actionable backlog items. • Remove blockers and escalate risks or delivery challenges proactively to the Head of Engineering. • Define and prioritize requirements for AWS-native data ingestion pipelines, ETL/ELT workflows, and data lake architecture, in close collaboration with Data Engineers. • Own the data catalog and governance backlog, ensuring data assets are documented, discoverable, and reliable for downstream consumers. • Drive requirements for data quality frameworks, monitoring, and SLA definitions across platform pipelines. • Partner with Application Engineering to ensure data products and APIs are integrated effectively into customer-facing and internal systems. • Translate business and analytical requirements from Data Analysts and Product Managers into clearly defined data product specifications, including datasets, APIs, and dashboard-ready outputs. • Define success metrics for data products and monitor adoption, quality, and performance post-launch. • Ensure data products meet the latency, reliability, and scalability requirements of a high-volume SaaS environment. • Collaborate with the Product Management team and Solutions Architecture to maintain a coherent data platform roadmap, balancing near-term delivery with long-term platform health. • Serve as the primary point of contact for Implementation and Support teams on data-related questions, bugs, and feature requests. • Provide regular, transparent updates on platform progress, risks, and upcoming milestones to Engineering leadership and cross-functional stakeholders. • Gather feedback from internal and external data consumers to inform continuous platform improvement.

We are looking for a Junior Data Engineer to design, develop, and optimize our data infrastructure on Databricks. You will be involved in architecting pipelines using BigQuery, Google Cloud Storage, Apache Airflow, dbt, Dataflow, and Pub/Sub, ensuring high availability and performance across our ETL/ELT processes. A successful candidate has knowledge of cloud-native data solutions, experience with ETL/ELT frameworks, and a passion for building robust, cost-effective pipelines.  Key Responsibilities Data Architecture - Support the development and maintenance of our data platform on GCP, including data warehousing in BigQuery/Databricks and data lake storage in Google Cloud Storage. - Help organize data into clear layers and domain-focused Data Marts for analytics and reporting. - Assist with Terraform-based Infrastructure as Code to provision and manage cloud resources in a consistent way. - Contribute to batch and near real-time data workflows with a focus on reliability, scalability, and cost awareness. Pipeline Development & Orchestration - Build, maintain, and improve ETL/ELT pipelines under guidance using Apache Airflow for workflow orchestration. - Develop and maintain dbt transformations to create clean, version-controlled data models in BigQuery. - Support data ingestion and processing using tools such as Google Dataflow, Apache Beam, or Pub/Sub where needed. - Monitor scheduled jobs, troubleshoot failures, and help ensure data is delivered on time for analytics and reporting. Data Quality, Governance & Security - Help implement and maintain data quality checks using Great Expectations, dbt tests, or similar tools. - Support documentation of datasets, metadata, lineage, and audit processes. - Follow security best practices, including IAM, encryption, and secure handling of sensitive data. - Assist in maintaining compliance with data privacy and governance requirements such as GDPR or CCPA. Scientists & Analytics Enablement - Partner with Analytics, Product, and Data Science teams to provide reliable datasets for dashboards, reporting, and experimentation. - Help maintain Data Marts that support key business domains and stakeholder needs. - Support data availability and accessibility for analytics and machine learning use cases. - Learn from senior team members and grow into owning larger parts of the data platform over time.

🔥 ¡ÚNETE A COVALTO Y FORTALECE NUESTRA INFRAESTRUCTURA TECNOLÓGICA! Ingeniero Infraestructura 📍 100% Remoto desde Colombia | 💻 Infraestructura & Cloud | ⚙️ Virtualización, Automatización y DevOps ¿Te apasiona la infraestructura, la automatización y la estabilidad de plataformas tecnológicas? ¿Quieres formar parte de una fintech que está transformando la banca en México desde la tecnología? ¡Esta oportunidad es para ti! En Covalto, impulsamos soluciones financieras digitales seguras y escalables, respaldadas por una infraestructura robusta, moderna y en constante evolución. 🚀 🧩 ¿Quiénes somos? En Covalto somos una fintech que impulsa el crecimiento de las PyMEs en México mediante soluciones financieras digitales ágiles y seguras. Nuestro compromiso es claro: innovar con responsabilidad, escalabilidad y excelencia operativa. Aquí, tu trabajo impacta directamente en la estabilidad y crecimiento de nuestra plataforma tecnológica. 💻✨ 🎯 ¿Cuál será tu misión? Como Especialista de Tecnología e Infraestructura, tu misión será asegurar la estabilidad, disponibilidad y mejora continua de las plataformas basadas en servidores virtuales, mediante la administración, mantenimiento y automatización de la infraestructura, aplicando buenas prácticas en Linux, virtualización e infraestructura como código, y contribuyendo activamente a la operación diaria del equipo de infraestructura y operaciones, evolucionando progresivamente hacia mayor autonomía técnica. 🛠️ ¿Qué harás en este rol? ➡️ Administrar y mantener la infraestructura virtual (principalmente en Sangfor y otras plataformas virtualizadas o cloud). ➡️ Gestionar servidores Linux y entornos LAMP en desarrollo, testing y producción. ➡️ Colaborar en la implementación de Infraestructura como Código y automatización con Ansible. ➡️ Administrar bases de datos y apoyar en configuraciones de networking (DNS, VLANs, firewall). ➡️ Operar herramientas de monitoreo y dar seguimiento a alertas e incidentes. ➡️ Participar en despliegues automatizados (CI/CD), gestión de repositorios Git y soporte a entornos Docker y Kubernetes. 🧠 ¿Qué buscamos? Una persona analítica, estructurada y orientada a la mejora continua, con mentalidad DevOps, enfoque en estabilidad operativa y capacidad para trabajar en equipo mientras desarrolla mayor autonomía técnica. 📋 Requisitos 🎓 Licenciatura en finanzas ingeniería de sistemas, ingeniería electrónica, actuaria, economía u otras disciplinas cuantitativas. 💼 3 a 5 años de experiencia en roles similares. 🐧 Experiencia comprobable en administración de servidores Linux. 🗄️ Experiencia en configuración y mantenimiento de entornos LAMP. 🛢️ Conocimientos prácticos en MySQL, PostgreSQL y MongoDB. 🐳 Experiencia en Docker (construcción y modificación básica de imágenes y Dockerfiles). 🌿 Manejo sólido de Git (branching y resolución básica de conflictos). ☁️ Conocimientos en Infraestructura como Código (nivel operativo). 🌐 Conocimientos en networking (subneteo, routing, DNS y switching). ⚙️ Capacidad para leer e interpretar playbooks de Ansible. 🖥️ Experiencia en virtualización con Sangfor, VMware o plataformas cloud. ✨ Deseables ☁️ Experiencia con servicios en GCP o AWS. 📊 Experiencia en herramientas de monitoreo empresarial. ☸️ Conocimientos básicos en Kubernetes. 🔄 Experiencia en herramientas de CI/CD. 🪪 Administración básica de Active Directory y LDAP. ⚖️ Experiencia con balanceadores de carga (Nginx o Apache). 🔐 Conocimientos en seguridad de infraestructura y manejo de SSL/TLS. 💾 Experiencia con herramientas de backup. 📊 Nivel avanzado en Microsoft Office. 📈 Conocimientos sólidos en análisis financiero y modelación. 🎁 ¿Qué te ofrecemos? 🏡 Esquema 100% Remoto en Colombia. 💵 Sueldo competitivo acorde a tu experiencia. 📈 Oportunidades de crecimiento en una fintech en expansión. 🧠 Cultura de mejora continua, automatización e innovación tecnológica. 🤝 Un equipo colaborativo que valora la excelencia técnica y el aprendizaje constante. 💬 ¿Listo para el reto? Si buscas un rol donde tu experiencia en infraestructura y automatización impulse la estabilidad de una fintech en crecimiento, en Covalto te estamos esperando. Estamos construyendo el banco del futuro. Hoy. ¿Te unes? 🚀 En Covalto estamos orgullosos de ser una empresa en donde prevalece la diversidad, la inclusión y la igualdad de oportunidades, independientemente del origen y condición ya que los colaboradores son prioridad para nosotros.