Role Description We are seeking an ETL Specialist who will play a key role in ensuring the secure, accurate, and efficient transfer of digital files from various veterinary Practice Information Management Systems (PIMS) to business partners. This role requires strong technical skills, a structured and detail-oriented approach, and the ability to work effectively across multiple file sources, tools, and environments. Success in this role means consistently delivering complete and high-quality attachment sets, maintaining efficient and standardized workflows, identifying data issues proactively, and collaborating closely with cross-functional teams. This is a full-time, remote position ideal for someone who thrives in technical environments and enjoys problem-solving. Responsibilities - Collect, extract, and migrate attachment files referenced within veterinary PIMS systems. - Retrieve files from various sources, including on-premises PIMS servers, email-delivered download links, and internal applications. - Perform file conversions, naming normalization, and file-type modifications as needed. - Validate file integrity, identify missing or inaccessible files, and communicate limitations to relevant stakeholders. - Use scripting tools (PowerShell or Python) to build or modify custom automation workflows. - Apply ELT (Extract, Load, Transform) concepts to streamline file handling and transformation processes. - Execute secure file transfers using SFTP, HTTPS, and token-based authentication. - Utilize cloud storage platforms, remote-access utilities, and data-management tools to retrieve and deliver files. Requirements - Experience working with Windows and macOS environments. - Proficiency in PowerShell and/or Python for scripting and automation. - Understanding of ELT concepts and their practical application. - Experience with cloud services such as: - Microsoft Azure - Microsoft Storage Explorer - Amazon S3 - Familiarity with remote-access and data transfer tools including TeamViewer, AnyDesk, Cloudberry, FileZilla, AzCopy, and Remote Desktop. - Proficiency with productivity and communication tools: Microsoft Teams, Office, Outlook, Jira. - Familiarity with database browsing tools such as DBeaver. - Basic understanding of secure data transfer protocols. Nice to Have - Previous experience in veterinary PIMS data handling or data migration. - Experience with file-based extraction from legacy systems. - Exposure to cloud-based storage workflows or enterprise data migration pipelines. - Familiarity with generative AI tools for documentation, automation, or workflow enhancement. - Experience working in fast-paced or mid-sized technical environments. Benefits - Competitive compensation and benefits package. - Opportunities for growth and professional development/continuous learning. - Flexible work arrangements. - Comprehensive leave policies, including PTO & holidays. - Monthly connectivity allowance.

Role Description As a Data Engineer, you will play a key role in creating, migrating, and maintaining regulatory reporting systems on Google Cloud Platform (GCP). - The Regulatory Data team is responsible for building and maintaining near real-time and batch reporting systems to fulfill regulatory requirements. - The team utilizes complex business logic to transform internal data models into those required by industry regulators and third parties. - You will support the migration from on-premise SQL Server systems to GCP as the team creates new GCP reporting systems. - Develop new cloud-native solutions and explore AI-driven development and automation to improve efficiency, consistency, and reliability across the team's processes. Qualifications - Experience with Google BigQuery. - SQL development experience, with the ability to write complex queries, stored procedures, and performance-tune data-intensive workloads. - Familiarity with GCP services such as Cloud Storage, Cloud Functions, Pub/Sub, or Cloud Composer. - Experience with data pipeline development (ETL/ELT) and orchestration tooling. - Exposure to Infrastructure as Code such as Terraform, and CI/CD pipelines such as Git, GitLab. - Methodical, with high attention to detail and the ability to break down complex requirements into simple solutions. - Interest in AI-assisted development tooling, such as Claude Code. - Ability to work to deadlines in a fast-paced, reactive environment. - SQL Server experience to support legacy systems during migration. Requirements - Developing and maintaining regulatory data submission systems, both existing on-premise and new cloud-based solutions in GCP/BigQuery. - Building and maintaining automated data pipelines for ingestion, transformation, and loading of regulatory data. - Supporting the migration of legacy SQL Server solutions to BigQuery, working closely with seniors and technical leads on architecture and data modelling. - Implementing data validation, monitoring, and alerting to ensure accuracy, consistency, and reliability of regulatory submissions. - Leveraging AI tooling, such as Claude Code, and contributing to the team's automation strategies to reduce manual effort and improve quality. - Participating in code reviews and adhering to departmental standards and the development process. - Conducting QA to ensure solutions are accurate, efficient, and performant. - Creating and maintaining relevant documentation. - Collaborating with other team members to deliver high-quality solutions within required timeframes. Benefits - Creating an environment where everyone feels welcome, respected, and valued. - Opportunities for growth and development, regardless of background. - Commitment to continuous improvement and striving to be better.

• Build data ingestion pipelines to extract and transform enterprise data. • Implement data cleansing and normalization routines. • Write and maintain ETL jobs using Spark/PySpark on cloud infrastructure. • Implement data validation and quality checks at each pipeline stage. • Build automated data export jobs for model training datasets. • Support feature extraction from enterprise schemas. • Monitor pipeline health, troubleshoot failures, and optimize performance. • Document data lineage, schemas, and transformation logic.

• Diseñar, desarrollar, implementar y ajustar sistemas distribuidos a gran escala y canalizaciones que procesan grandes volúmenes de datos • Centrándose en la escalabilidad, la baja latencia y la tolerancia a fallos en cada sistema construido