• Design and deploy scalable Google Cloud services in GCP. • Implement IAM access controls to ensure secure and compliant data environments. • Develop and implement robust data ingestion pipelines from diverse sources. • Develop and enforce data validation processes to maintain accuracy and reliability. • Enhance data quality and efficiency through continuous optimization. • Analyze raw data to uncover patterns, trends, and opportunities. • Produce clear design documentation and solution roadmaps. • Lead projects independently while collaborating effectively within larger teams. • Mentor and cross‑train junior and senior Data Engineers, sharing expertise on complex assignments. • Advance your skills through hands‑on experience and formal learning opportunities. • Support pre‑sales activities by providing accurate work estimates and technical input. • Partner closely with Project Management to deliver projects on time and within budget. • Travel occasionally as required for project or team needs.

• As a Senior Data Engineer at Orijin, you will be a technical leader responsible for building, scaling, and modernizing the company’s data platform. • Your primary focus will be on data modeling, pipelines, architecture, reliability, and performance, ensuring that data is trusted, timely, and production-ready. • As a member of the Enterprise Services team, you will partner closely with data analysts, engineers and product managers to shape how data is modeled and used. • You will bring an analytical mindset to pipeline design and enable high-quality insights across the organization. • You will ensure company-wide confidence in data quality and enable data-enabled differentiating products and services. • Design and evolve Orijin’s data architecture to support scalability, reliability, and near–real-time use cases. • Define standards for data modeling, orchestration, versioning, and deployment. • Own the design, build, and maintenance of production-grade data pipelines across batch and streaming workloads. • Architect and maintain data systems using tools such as AWS (S3, RDS, Redshift, Lambda, DMS, Glue etc.).

• Lead technically the team and enable a multidisciplinary team of data scientists and data engineers to build, enhance, and maintain data products. • Visit our European clients a few weeks throughout the year in order to bootstrap projects, establish and expand relationships with key technical and non-technical stakeholders • Work on a variety of projects, for different clients, in different subject matter domains. • Participate in design and architecture discussions. • Collaborate with strategy, customer experience, product and non-technical program management teams. • Ensure that solutions are following security and performance best practices. • Create & maintain design and other documentation required by the clients. • Communicate with customer’s team members and align technical solutions. • Understand requirements and make viable technical solutions choosing appropriate frameworks. • Guarantee a stable and productive development environment.

• Design and execute technical processes to migrate data from Oracle (Clarity) to Google BigQuery. • Handle complex schema mappings, specifically resolving incompatibilities between Oracle data types and BigQuery (e.g., handling timestamps, numerics, and character sets). • Troubleshoot pipeline failures related to hardware latency and legacy infrastructure constraints. • Develop automated SQL scripts and testing frameworks to validate data replication accuracy at scale. • Perform deep-dive root cause analysis on data inconsistencies, distinguishing between genuine data errors and artifacts of the conversion process. • Create technical documentation for data lineage and conversion logic. • Optimize SQL queries for performance within the BigQuery environment to manage costs and reduce latency. • Collaborate with Data Analysts to verify business logic and ensure the migrated data meets clinical reporting standards.