Senior Engineering Manager – Data Architecture

Abbott • CA

82d • $146,700 - $293,300

About The Position

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 114,000 colleagues serve people in more than 160 countries. 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. You’ll also have access to career development with an international company where you can grow the career you dream of. Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical 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 bachelor’s 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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• Free medical coverage in our Health Investment Plan (HIP) PPO medical plan.
• Excellent retirement savings plan with a high employer contribution.
• Tuition reimbursement and the Freedom 2 Save student debt program.
• FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees