Data Operations Lead

This is a fully remote position, open to applicants in Germany.

📋 Description

• Data Partnership Operations & Lifecycle Management: Take ownership of the operational lifecycle for external data partnerships from the point of contract signing. Serve as the main operational and technical liaison for hospitals, biobanks, CROs, and research laboratories. Oversee onboarding, data delivery schedules, and stakeholder communication to guarantee the successful achievement of partnership milestones.

• Data Transfer & Infrastructure Coordination: Oversee secure biomedical data transfers utilizing cloud infrastructure and standardized transfer protocols. Manage access control, encryption, and ingestion workflows across various cloud storage systems (AWS S3, SFTP, APIs, direct upload pipelines). Ensure the delivery, validation, and tracking of incoming datasets in accordance with internal governance standards.

• Clinical & Multi-Omics Data Harmonization: Work in conjunction with internal technical and product teams to define and uphold harmonized data models and metadata standards across intricate clinical and multi-modal datasets. Organize and sustain connections between clinical metadata and related omics or imaging assets, encompassing genomics, transcriptomics, spatial biology, and pathology data.

• Pipeline Operations & Automation: Collaborate closely with engineering and data teams to configure and uphold lightweight ingestion and QC pipelines. Identify operational bottlenecks and repetitive workflows, converting them into scalable systems, scripts, templates, dashboards, or automation tools to enhance operational efficiency and visibility.

• Data Quality Oversight: Coordinate both automated and manual quality control checks on incoming datasets. Detect missing data, inconsistencies, corruption, or metadata mismatches and engage directly with external partners to address these issues. Ensure data integrity, traceability, and version control throughout the ingestion process.

• Operational Tracking & Reporting: Maintain a centralized "single source of truth" for all incoming datasets, which includes ingestion status, completeness, QC status, and milestone tracking. Develop and sustain reporting dashboards and operational tools to enhance transparency into project progress, ingestion velocity, and operational risks.

• Cross-Functional Collaboration & Communication: Collaborate closely with Data Science, Engineering, Legal, and Partnership teams to ensure operational execution aligns with business and scientific priorities. Clearly communicate technical issues to both scientific collaborators and non-technical stakeholders. Provide regular updates regarding operational risks, blockers, and delivery progress.

• Site Visits & External Partner Engagement: Conduct periodic visits to partner hospitals, biobanks, and laboratories to assist in onboarding, resolve technical or operational challenges, and strengthen long-term collaborations.

⛳️ Requirements

• Biomedical Data Expertise: Strong knowledge of clinical and biomedical data structures, including real-world data, clinical trial datasets, and multi-omics data modalities. Familiarity with oncology, immunology, or related therapeutic fields is highly advantageous.

• Cloud & Data Infrastructure: Demonstrated experience in managing data lifecycles within cloud environments, particularly AWS (S3, CLI, access management). Knowledge of secure data transfer protocols and large-scale biomedical data handling workflows is essential.

• Data Wrangling & Technical Skills: Proficient in Python or R, along with SQL for querying and transforming datasets. Capable of writing lightweight scripts, automating workflows, and interacting with APIs or cloud-based systems.

• Project & Stakeholder Management: Proven ability to manage multiple external collaborations and operational workstreams concurrently. Exceptional communication skills, with the capability to translate technical issues into clear guidance for both scientific and non-technical stakeholders.

• Operational Problem Solving: Comfortable working independently in ambiguous environments. Strong analytical and organizational skills with the ability to identify bottlenecks, enhance processes, and promote operational efficiency.

• Educational Background: Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Health Informatics, Computer Science, or a related quantitative discipline.

🏝️ Benefits

• Competitive salary and equity package

• Flexible work arrangements, including remote options

• Opportunities for professional growth and leadership development