Seeking an experienced and visionary Engineering Manager to lead a Data Platform team through a transformation from a service-oriented model to a product-oriented platform team focused on automation, scalability, integration, and AI-driven product products.
Locations (3)
Barcelona, Catalonia, Spain
Berlin, Germany
Vienna, Vienna, Austria
Responsibilities
Define and drive the strategic evolution of the team towards building a modern, scalable data platform that enables advanced data and AI use cases.
Enable development teams to safely and autonomously leverage data and platform capabilities through robust tooling, guardrails, and well-defined interfaces.
Establish a long-term roadmap that aligns data platform capabilities with emerging AI use cases, product needs, and regulatory constraints.
Build and grow a high-performing, cross-functional team capable of delivering reliable, scalable, and compliant platform solutions.
Shape the team’s culture by promoting initiative, critical thinking, technical leadership, and shared responsibility.
Lead privacy-centric engineering initiatives within JPMorgan Chase’s Chief Data & Analytics Office, managing the Data Privacy & Governance roadmap and driving technical direction for privacy impact assessments and technology integrations.
Responsibilities
Manage the Data Privacy & Governance roadmap
Lead firmwide privacy initiatives
Drive technical direction for Privacy Impact Assessment
Structure roadmap delivery and operating model
Oversee engineering projects, risks, issues, and dependencies
Requirements
Nice to have: Complex data governance
Nice to have: Security and compliance requirements
Own the vision, strategy, roadmap and requirements for the oncology data platform, aligned with N-Power's business goals.
Compensation
The expected salary range for this position is $167,777 - $215,304. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.
Responsibilities
Own the vision, strategy, roadmap and requirements for the oncology data platform, aligned with N-Power's business goals and the needs of our ProECA studies.
Manage the platform as a product: define its customers (biostatisticians, quantitative scientists, clinical operations, and pharma sponsors), set success metrics, and track adoption and value.
Collaborate with a cross-functional team of engineers, data architects, informaticists, AI engineers, quantitative scientists, clinical abstractors, and medical oncologists.
Build regulatory-grade evidence into the platform: source-to-dataset traceability across EHR and imaging, data provenance, audit trails, and fit-for-purpose data quality aligned with FDA guidance on external controls.
Catalog and be able to point to end-user documentation for each data platform release: data dictionaries, vocabularies, CDISC-aligned specifications, data quality scorecards, licensing, and de-identification certifications.
Requirements
Nice to have: oncology drug development lifecycle
Nice to have: prospective clinical research operations
Lead Data Engineer responsible for designing and building CheQ’s data platform, establishing architecture, governance, and scaling the data engineering function.
Responsibilities
Design target-state data architecture and roadmap
Define business data layer and modeling
Establish data quality, lineage, and governance
Enable analytics and self-service
Prepare AI/ML readiness
Requirements
Nice to have: Series B/C fintech experience
Nice to have: AI/ML workload design
Nice to have: batch/streaming/transactional patterns
Lead complex, multi-disciplinary projects in the Data Cloud portfolio, driving execution, communication, and planning for Data Cloud products and services.
Enable execution across multiple teams and drive delivery across the complete portfolio of Data Cloud products and solutions.
Engage with engineering directors, product leaders and other TPM groups to streamline processes, simplify execution, manage Objectives and Key Results (OKRs), release on time, leverage AI tooling for efficiencies and help the teams you are engaged with in execution.
Mentor junior team members, act as a role model and advocate for the Technical Program Manager (TPM) role.
Requirements
Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or related technical field
Nice to have: integrating GenAI/LLM capabilities into data products
Nice to have: leveraging AI tooling to automate program workflows
Nice to have: partnering with executive Engineering Directors and VP/Product leaders
Drive large-scale data platform modernization and AI enablement for clients operating complex, distributed data environments, including federal and defense environments with classified and cross-boundary data.
Responsibilities
Lead data platform architecture and engineering assessments, including current-state analysis, target-state design, and modernization roadmaps.
Design AI/ML enablement architectures that support scalable model development, deployment, and monitoring across hybrid and multi-cloud environments.
Assess data governance and AI readiness and develop implementation roadmaps aligned with compliance and business timelines.
Evaluate dependencies between data platform modernization and AI/ML initiative sequencing.
Assess AI infrastructure readiness, including compute, power, networking, and hosting boundaries, alongside the data center and network leads.
Engineering Manager - Data PlatformN26 · Barcelona, Spain+2 more
Senior Director of Software Engineering - Privacy Engineering LeadJPMC Candidate Experience page · London, United Kingdom
Staff Oncology Data Product ManagerN-Power Medicine · Redwood City, US
Data Engineering Manager (Data Platform)Funding Circle · London, United Kingdom
Technical Program Manager, Big Data and AnalyticsGoogle · Sunnyvale, US
Senior Data Platform & AI LeadStrategic Growth Partners · Washington, US