Senior Engineering Manager – Data Architecture

JOB DESCRIPTION:

Working at Abbott

At Abbott you can do work that matters grow and learn care for yourself and your family be your true self and live a full life. Youll also have access to:

• Career development with an international company where you can grow the career you dream of.

• Employees can qualify forfree medical coverage in ourHealth Investment Plan (HIP) PPOmedical plan in the next calendar year.

• An excellent retirement savings plan with a high employer contribution.

• Tuition reimbursement the Freedom 2 Save student debt program and FreeU education benefit - an affordable and convenient path to getting a bachelors degree.

• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.

The Opportunity

Lingo is building the future of personal health insights through always-on biosensor data real-time analytics and personalized recommendations. Our platform ingests millions of readings daily delivering clinically relevant insights to consumers and partners across the globe. As we expand across multiple regions data architecture is mission-critical ensuring our systems are scalable secure compliant and able to power innovation across product marketing and R&D.

We are seeking a proven leader to own and evolve Lingos multi-region enterprise data platform. This role will drive the enterprise data architecture that powers Lingos growth and trusted insights. Your decisions will enable global scale accelerate product innovation and deliver real-time reliable analytics to customers and partners. As we expand this role offers a path to Director-level leadership and broader influence across our global data footprint.

What Youll Work On

• Own the enterprise data reference architecture and roadmap across operational analytical and ML domains; ensure interoperability consistent metadata and scalable data contracts.
• Architect and evolve event-driven pipelines (Kafka Databricks/Spark analytics stores) and CDC pathways for real-time and batch workloads with HA/DR patterns.
• Design data architectures optimized for AI/ML workloads; enable seamless integration of models into batch and streaming pipelines for real-time insights.
• Leverage Azure and Databricks to support AI-driven decision-making and predictive analytics; partner with data science to operationalize models using event-driven architectures and modern orchestration tools.
• Champion best practices for governance quality lineage and retention to power trustworthy AI applications; implement automated auditable controls that ensure HIPAA/GDPR compliance-by-design.
• Define and track data SLOs (freshness accuracy availability latency cost); lead capacity planning observability and incident playbooks for data services.
• Design storage strategies for performance and cost (partitioning sharding tiered storage) and tune databases for high-volume time-series and transactional workloads; plan for scale (e.g. 100M daily biosensor readings across regions).
• Foster a data-driven culture: promote data literacy launch training programs and evangelize best practices across engineering product and business teams.
• Collaborate cross-functionally with Backend Cloud/Platform Security Product and Compliance to remove obstacles in a regulated medical device software environment.
• Lead and mentor the data engineering team; establish standards conduct reviews and drive continuous improvement in delivery and reliability.

Required Qualifications

• 10 years in data architecture for high-volume distributed systems including multi-region production platforms.
• Deep expertise in event streaming and large-scale ETL/ELT with Kafka and Databricks or Spark; strong SQL and data modeling (3NF dimensional time-series).
• Hands-on experience optimizing databases indexing storage tiers and CDC patterns.
• Proven track record implementing automated governance lineage and compliance frameworks (HIPAA GDPR) in enterprise environments; ability to support trustworthy AI through rigorous data controls.
• Experience enabling AI/ML workloads in production (feature pipelines model data interfaces real-time inference).
• Demonstrated success in regulated environments; understands medical device software realities and how to stay compliant while shipping quickly.
• Strong cross-functional leadership and stakeholder alignment; effective at road mapping trade-offs and communicating impact to business outcomes.
• Team leadership: mentoring engineers establishing standards and improving team velocity and quality.
  

Preferred Qualifications

• Experience in digital health Medtech or other regulated SaaS environments; familiarity with BI tooling analytics APIs and self-service strategies.
• Azure and Databricks experience; exposure to service meshes/Kubernetes and cloud-native data platform patterns; cost optimization at scale.
• Experience with ML feature stores model-serving data interfaces or metrics platforms. Knowledge of data mesh principles enterprise metadata management and federated governance.
• Track record fostering data literacy and running enablement programs across teams.

Learn more about our health and wellness benefits which provide the security to help you and your family live full lives:

Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer committed to employee diversity.

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The base pay for this position is

In specific locations the pay range may vary from the range posted.

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