Senior Data Engineer

About Us At Prenuvo , we are on a mission to flip the paradigm from reactive “sick-care” to proactive health care. Our award-winning whole body scan is fast (under 1 hour), safe (MRI has no ionizing radiation), and non-invasive (no contrast). Our unique integrated stack of optimized hardware, software, and increasingly AI, coupled with the patient-centric experience across our domestic and global clinics, have allowed us to lead the change against “we caught it too late again". We are looking for a Senior Data Engineer to build reliable, scalable data products that connect Prenuvo's Growth/Marketing technology into a trusted enterprise view. This role does not provide visa sponsorship. Applicants must be legally authorized to work in the United States at the time of hire and must not require employer sponsorship for a work visa (current or future). Help reshape the world through proactive healthcare while working with cutting-edge technology and high performing teams with deep expertise - join us to make a difference in people’s lives! What You'll Do - Design, build, and own production grade data pipelines connecting marketing data, event tracking, and other data sources into Databricks. - Create durable data models that connect campaign and channel exposure to website behavior, leads, bookings, completed scans, revenue, and repeat activity. - Partner with Marketing, Product, Engineering, Privacy and Security on event taxonomy, identity resolution, consent aware data flows, and source system contracts. - Improve conversion and attribution data quality across online and sales assisted journeys, including reliable downstream signals for supported media and lifecycle platforms. - Implement automated testing, freshness monitoring, alerting, lineage, and incident response practices for critical Growth data products. - Replace fragile custom transformations and manual workarounds with documented, reusable, reviewed code. - Contribute Growth measures and dimensions to the governed semantic layer so definitions remain consistent across analysis, dashboards, and activation. - Review technical work, share context, and improve team standards without becoming a single point of dependency.

What You’ll Bring - At least 4 years of experience in data engineering, analytics engineering, or a closely related data role. - Advanced SQL and strong Python skills, with experience building maintainable production data pipelines. - Hands on experience with a cloud data platform and modern transformation framework. Databricks and dbt experience are strongly preferred. - Hands on experience building and operating production data pipelines using ingestion and orchestration tools such as Fivetran or Apache Airflow, including monitoring, dependency management, schema changes, failure recovery, and data quality controls. - Experience integrating APIs, SaaS systems, event data, and operational databases into an analytical platform. - Strong knowledge of data modeling, orchestration, testing, observability, version control, code review, and continuous delivery practices. - Ability to translate ambiguous Growth questions into reliable data products while balancing speed, privacy, and long term maintainability. - Clear communication skills and experience working across Marketing, Product, Engineering, Analytics, and business stakeholders. - A platform builder mindset with strong ownership, practical judgment, and attention to data quality. Nice to Have - Experience with Salesforce, PostHog, Google Analytics, Google Tag Manager, Iterable, Workato, or reverse data movement tools. - Familiarity with conversion APIs, server side signaling, UTM and click identifier flows, or media platform integrations. - Experience in healthcare, another regulated environment, or privacy sensitive customer data. - Experience designing event taxonomies and behavioral data contracts.