Senior Data Platform Engineer - Milan

<p><span><span><b>Additional Locations:</b></span></span> France-Île-de-France; Germany-Düsseldorf; Italy-Milan; Netherlands-Kerkrade; Spain-Madrid; United Kingdom-Hemel Hempstead</p> <p><span><span><b>Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance</b></span></span></p> <p><span><span>At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.</span></span></p> <p><span>A <strong><em>Day in the Life</em></strong> of the EMEA Data Platform Engineer: </span></p> <p><span>You’ll start your day by scanning platform health dashboards, pipeline success rates, latency, cost and capacity signals, SLO attainment, and data quality alerts, then action the highest</span><span>‑</span><span>value improvements. You</span><span>’</span><span>ll partner with data product managers &amp; owners, data engineers, AI engineers, data scientists, and application teams to turn business needs into robust, reusable platform capabilities.</span></p> <p> </p> <p><span>When EMEA</span><span>‑</span><span>specific constraints (e.g., GDPR) surface, you</span><span>’</span><span>ll collaborate with Security, Legal, and Governance to design compliant patterns without slowing delivery. Working closely with the Global team, you</span><span>’</span><span>ll ship infrastructure</span><span>‑</span><span>as</span><span>‑</span><span>code, automate CI/CD for data workloads, and harden security so teams can build safely by default.</span></p> <p> </p> <p><span>Throughout the week, you’ll evolve ingestion and processing frameworks (batch, micro</span><span>‑</span><span>batch, streaming), improve observability (logging, tracing, lineage), and coach teams on using the platform</span><span>’</span><span>s self</span><span>-</span><span>service tooling and catalog. You</span><span>’</span><span>ll run blameless incident reviews, remove toil, and continuously raise reliability, performance, and cost efficiency.</span></p> <p> </p> <p><span>Each month, you’ll contribute to global architecture forums to converge standards, reuse patterns, and ensure EMEA requirements are reflected in the enterprise roadmap.</span></p> <p> </p> <p><strong><span>The role:</span></strong><span><br/>Reporting to the Data Engineering &amp; Platform Manager, the Data Platform Engineer builds and operates the cloud data platforms that powers analytics, AI, and operational data products across the region. You will design secure, scalable, and observable platform services (compute, storage, processing, orchestration, quality, lineage, access), deliver them as well</span><span>‑</span><span>documented, reusable capabilities, and support teams in adopting them at scale. Success requires deep engineering craft, platform thinking, and close collaboration across product, architecture, and governance.</span></p> <p> </p> <p><strong><span>Key Responsibilities:</span></strong></p> <ul> <li><span>Platform engineering &amp; operations: Design, build, and operate cloud data platforms components (lake/lakehouse, warehouses, streaming, orchestration, catalogs) with strong SLIs/SLOs, automated recovery, and capacity planning.</span></li> <li><span>Pipelines &amp; frameworks: Provide reusable templates and libraries for ELT/ETL, CDC, and streaming, standardize patterns for schema evolution, testing, and deployments across domains.</span></li> <li><span>Security &amp; compliance by design: Implement least</span><span>‑</span><span>privilege IAM, key management, encryption in transit/at rest, network segmentation, and data classification, ensure GDPR/data residency adherence with auditable controls.</span></li> <li><span>Observability &amp; quality: Instrument end</span><span>‑</span><span>to</span><span>‑</span><span>end telemetry (logs/metrics/traces), lineage, and data quality checks, build dashboards and alerts to prevent regressions and reduce MTTD/MTTR.</span></li> <li><span>Automation &amp; IaC: Deliver platform resources with infrastructure</span><span>‑</span><span>as</span><span>‑</span><span>code, enable Git</span><span>‑</span><span>based workflows, CI/CD for data workloads, and policy</span><span>‑</span><span>as</span><span>‑</span><span>code guardrails.</span></li> <li><span>Cost efficiency: Monitor and optimize spend across compute/storage, set budgets and alerts, recommend right</span><span>‑</span><span>sizing, workload scheduling, and caching/format strategies.</span></li> <li><span>Collaboration &amp; enablement: Document platform capabilities, publish examples and runbooks, and provide office hours/community support to drive safe self</span><span>‑</span><span>service adoption.</span></li> <li><span>Inciden