We are seeking a Lead Data Engineer to architect, build, and scale our next-generation healthcare data platform. In this role, you will lead the effort to design robust pipelines, modernize data architecture, and ensure high-quality ingestion and transformation of clinical and operational data. You’ll collaborate closely with product, analytics, clinical informatics, machine learning, and engineering teams to deliver trusted, timely, and compliant insights. This is a hands-on leadership role ideal for someone who enjoys setting technical direction while still contributing code and guiding stakeholders through complex healthcare data challenges. Responsibilities Architecture & Strategy - Lead design and evolution of our cloud-native data platform built primarily on Google Cloud Platform, including BigQuery, Cloud Storage, Pub/Sub, Cloud Run, Airflow (Cloud Composer), and Healthcare API. - Inform strategic decisions around multi-cloud or AWS interoperability when needed. - Establish data engineering best practices, coding standards, and architectural patterns. Pipeline Development - Build scalable ETL/ELT pipelines using dbt for transformations and Airflow for orchestration. - Develop ingestion pipelines for clinical and administrative data in HL7, FHIR, DICOM, and custom formats. - Develop ingestion and transformation pipelines to be used for AI/ML development and model training. - Implement streaming and batch dataflows using Pub/Sub, Dataflow, and serverless compute. - Support or guide integrations with AWS-based partner systems or AWS-hosted data sources when applicable. Data Modeling & Warehousing - Design and maintain BigQuery datasets, semantic layers, and warehouse structures. - Leverage industry standards such as FHIR resources for canonical healthcare models. - Provide guidance on data modeling and warehouse best practices across both GCP and AWS ecosystems. Data Quality, Observability & Governance - Implement data quality frameworks, automated testing, and monitoring. - Ensure HIPAA compliance and proper handling of PHI/PII across all pipelines and cloud environments. - Drive lineage, documentation, metadata governance, and dbt docs adoption. Leadership & Collaboration - Partner with analytics, product, clinical informatics, and security teams to deliver high-quality, trustworthy data products. - Provide oversight and technical direction for multi-cloud data integrations with AWS-based systems or partners. - Assist in the recruitment and development of junior data engineers

• Architect, build, and scale healthcare data platform • Lead design and evolution of cloud-native data platform on GCP • Build scalable ETL/ELT pipelines using dbt and Airflow • Design and maintain BigQuery datasets and warehouse structures • Implement data quality frameworks and ensure HIPAA compliance • Partner with analytics and product teams to deliver data products • Provide oversight and technical direction for multi-cloud integrations

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Following our remarkable growth in Switzerland, Poland, and Germany, Unit8 is expanding into the US market. We are seeking a Senior Forward Deployed Engineer who will work directly with customers, owning delivery strategy and implementation. You will act as a thought leader and strategic force in a technical domain that is critical for Unit8 and its clients. You will collaborate closely with Unit8 CTO, our clients, and the Business Development organization to be on the forefront of extending Unit8’s strategy into the US market. What You'll do - As a core member of our agile project teams, you will be responsible for designing, building, and maintaining robust data solutions and infrastructure. - You will work on cutting-edge data and AI topics to solve real-world business problems for our clients. - Your responsibilities will include: - Developing, deploying, and troubleshooting complex data pipelines and processing systems using a variety of open-source and closed-source technologies, with a strong focus on Foundry. - Driving optimization, testing, and tooling to ensure exceptional data quality. - Collaborating with other software engineers, ML experts, and stakeholders in a cross-functional agile environment. - Working in multi-functional agile teams to continuously experiment, iterate and deliver on new product objectives. Qualifications - Deep Domain Expertise: Minimum 5 years of experience in software/data engineering or data science. - Commercial Fluency: Proven experience in pre-sales, proposal design, or technical advisory where you influenced executive decision-making. - GenAI/LLM Context: For relevant tracks, you have past experience building solutions with LLMs and a deep understanding of the overall GenAI landscape (Evaluation, Training, Problem Decomposition). Requirements - You have an engineering mindset focused on delivering working solutions. - You prioritize solving real business problems over theoretical perfection or academic benchmarks. - You are comfortable working in a dynamic environment with evolving objectives. - You can collaborate efficiently with both technical engineers and non-technical business stakeholders. - You feel a sense of ownership over the company’s technical reputation and are eager to train those coming up behind you. - Experience with programming/scripting, such as Python and/or SQL. - Proficiency in Palantir Foundry (nice-to-have). - Strong foundation in Computer Science, Mathematics, Physics, or related engineering fields. - Willingness to travel (min. 10%) to client sites to drive implementation success and build relationships. - Strong client-facing skills: You are comfortable interacting with both business and technical clients, giving presentations, and possess a strong problem-solving mindset. Benefits - High-Stakes Work: You will work on critical projects that transform how major industries operate. - A "Builder" Culture: We are not a slide-deck consultancy. We build things that work. You will be surrounded by engineers and data scientists who share your passion for execution. - Pioneering role and autonomy: As a key member of our US growth, you will have the freedom to shape how we deliver value in this new market. - Groundbreaking Opportunity: You will play a pivotal role in establishing Unit8's footprint in the USA, driving the growth and impact of our operations in this emerging market. - Rewarding Package: The estimated base salary range for this position is $120,000 – $150,000. In addition to base pay, total compensation includes an annual bonus based on individual and company performance. We also offer a 401(k) retirement plan and comprehensive health insurance. Final compensation will be determined based on the candidate’s qualifications, experience, and skills.

• Design, build, and operate data ingestion and ETL/ELT pipelines for our data systems that power Atto products and customer-facing applications. • Build and maintain our data platform architecture and infrastructure, including data pipelines, warehouses that power analytics and product features and reporting. • Implement data modelling, schema design, and data contracts to make datasets easy to consume. • Introduce and maintain observability, data quality checks, and automated testing for our production data flows. • Driving impact at scale by improving data workflows, service reliability, and making Atto’s capabilities faster, more reliable and widely accessible. • Collaborate with product managers and cross-functional teams to translate market signals and customers’ needs into innovative data-driven solutions. • Create new systems and approaches, while continuously improving and scaling existing ones for performance, reliability, and efficiency. • Conduct deep analysis of transactional datasets to validate data models, surface data quality issues, and propose engineering fixes. • Optimise performance and cost of data processing and storage across cloud services. • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across the business. • Stay current with industry developments, emerging technologies, and best practices in data engineering.