• Design, develop, and maintain robust, scalable data pipelines, ensuring integrity, performance, and availability • Work on ingestion, transformation, and integration of data from multiple internal and external sources • Actively contribute to the evolution of the data architecture, applying modern architecture principles (Lakehouse, data layering, distributed processing) • Build data infrastructure that supports growth, new products, and analytical demands with security and governance • Support analytical data modeling, ensuring technical structures correctly support business metrics and KPIs • Collaborate with Analytics Engineers and Data Analysts to enable consistent, reusable, and high-performance models • Ensure that data delivered for analytical consumption maintains quality standards and traceability • Implement and evolve pipeline monitoring and automated data validations, performing troubleshooting when necessary • Adopt best practices for data testing, versioning, and technical documentation • Act as a technical lead, supporting team development and the adoption of engineering standards

• Coordenar o time de Engenharia de Dados, garantindo alinhamento, priorização e entrega contínua • Atuar como referência técnica, apoiando decisões de arquitetura, padrões e boas práticas • Desenvolver o time por meio de feedbacks, acompanhamento técnico e apoio à evolução de carreira • Organizar backlog técnico, rituais de acompanhamento e alinhamento com o Head de Dados • Liderar a implementação e evolução de arquiteturas modernas de dados, garantindo escalabilidade, performance e governança • Definir e manter padrões de engenharia para ingestão, transformação, versionamento e publicação de dados • Garantir a integração eficiente de dados provenientes de múltiplas fontes internas e externas • Apoiar a construção e disseminação da cultura de engenharia e dados na Sólides

• Design, build, and maintain data pipelines using SQL, Python, dbt and Databricks. • Conduct regular data quality checks to ensure accuracy and integrity for downstream users. • Proactively identify data issues and develop custom solutions. • Monitor pipeline performance and tune processes to improve efficiency. • Work with cross-functional teams to understand data requirements and incorporate them into the data framework. • Actively participate in discussions, offering input and feedback to drive continuous improvement.

Role Description As a Senior Data Engineer (Platform) at Freshbooks, you will help shape the future of FreshBooks’ data engineering infrastructure and processes within the R&D organization. You will design and build scalable, reliable data pipelines and platforms on modern cloud infrastructure to power analytics, operations, and machine learning use cases. You will partner closely with Product, Data Analytics, Machine Learning, Platform, Infrastructure, and Security teams to deliver high-quality data solutions across the full data lifecycle. You will contribute to engineering standards, reliability practices, and incident response while mentoring other engineers. This role is ideal for someone who enjoys solving complex data challenges and raising the bar for engineering excellence. NOTE: This role can be worked remotely from the above location. What You’ll Do - Design, build, and operate batch and streaming data pipelines on GCP using Airflow (Cloud Composer), dbt, Datastream, Fivetran, Pub/Sub, Dataflow, BigQuery, and Cloud Functions - Build event-driven and near real-time ingestion and transformation workflows to support analytics, operations, and ML workloads - Develop and operate ML data and serving infrastructure using Vertex AI, Kubeflow, Cloud Run, and Cloud Composer for batch and real-time predictions - Implement CI/CD pipelines and infrastructure as code using tools such as GitHub Actions, Azure Pipelines, Terraform, and Terraspace - Drive observability, monitoring, alerting, security, and access controls using OpenTelemetry and cloud-native services - Partner with Product, Data Analytics, Machine Learning, Engineering, Platform, Infrastructure, and Security teams to design scalable, secure, and cost-efficient data systems - Lead design and code reviews, contribute to engineering standards, incident management practices, and mentor junior and mid-level engineers Qualifications - 5+ years of experience designing, building, and operating data pipelines and data platforms - Strong experience with batch and near real-time data processing and streaming architectures - Hands-on expertise with Google Cloud Platform or another major cloud provider (AWS or Azure) and cloud data warehouses (BigQuery, Snowflake, Redshift) - Expert SQL skills and strong programming experience in Python or similar languages - Experience with orchestration tools (Airflow or equivalent), CDC technologies, and event-driven systems - Experience with DevOps and IaC tooling (Docker, Kubernetes, Terraform, Jenkins, Git, CI/CD pipelines) - Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders You’ll Stand Out If You Have - Strong foundations in networking, cloud security, and access management (VPCs, IAM, ZTNA, DMZ) - A track record of staying current with modern data engineering platforms and best practices - Experience in SaaS or fintech environments