8 days ago
Base Salary
$99k - $199k/yr
Responsibilities
- Own technical design and hands-on delivery for complex data products, pipelines, integrations, and platform capabilities.
- Build and evolve documented, discoverable, governed, observable, and supportable domain data products.
- Define data contracts covering schemas, freshness, availability, breaking changes, and producer and consumer responsibilities.
- Design data products for analytics, machine learning, and AI consumption with reproducibility, lineage, timeliness, and data quality controls.
- Diagnose complex production and data quality issues and drive root-cause resolution.
- Manage technical cost efficiency through compute and warehouse sizing, job and query optimization, and serverless and storage tradeoffs.
- Work with business stakeholders and partner technology organizations to shape technical solutions and communicate tradeoffs.
- Lead design and code reviews, mentor engineers, and guide implementation without formal authority.
- Lead adoption and continuous improvement of testing, observability, CI/CD, and delivery practices.
- Implement appropriate controls for protected health information and sensitive data, including access control, masking, de-identification, lineage, retention, and audit support.
- Serve as a domain subject matter expert for significant production incidents and support compliance with quality management policies.
Requirements
- Bachelor's degree in Data Science, Computer Science, Information Systems, Mathematics, or Engineering.
- 8+ years of progressively responsible experience in data engineering or a closely related discipline.
- Experience owning technical design and hands-on delivery of complex data products, pipelines, or platform capabilities through production support.
- Advanced SQL and Python skills with relational, dimensional, and semi-structured data modeling experience.
- Experience designing and operating scalable distributed data systems on platforms such as Databricks and Spark, using AWS, Azure, or Google Cloud Platform.
- Experience with version control, automated testing, CI/CD, and orchestration or transformation tools such as Databricks Workflows, Delta Live Tables, Airflow, or dbt.
- Experience with governed data, cataloging, lineage, access control, and data quality capabilities such as Unity Catalog.
- Ability to partner with business stakeholders, translate needs into technical solutions, mentor engineers, and raise technical quality across a team.
- Preferred experience with streaming and event-driven architectures such as Kafka.
- Preferred experience in regulated environments involving HIPAA, CLIA, SOX, FDA, ISO 13485, or IEC 62304, ideally involving life sciences, diagnostics, clinical laboratory data, or protected health information.
- Preferred experience with semantic layers, metric definitions, data products, or feature pipelines supporting analytics, machine learning, and AI use cases.
- Preferred experience with Parquet, Avro, Delta Lake, REST API development, integration patterns, and business intelligence tools such as Tableau.
- Ability to perform the essential duties with or without accommodation.
Benefits
- The role is based in Madison, Wisconsin, with relocation assistance potentially available for qualified candidates.
- Standard work shift with travel required approximately 10% of the time.
- Continuous sitting and keyboard use are significant work activities for the position.
Tech Stack
Categories
Data Engineering
About Abbott
Abbott is a NYSE‑listed healthcare company that develops diagnostics, medical devices, nutrition products, and branded generic medicines for clinicians and consumers. Founded in 1888 and headquartered in Abbott Park, Illinois, it sells products in more than 160 countries, including the FreeStyle Libre continuous glucose monitoring system. Revenue comes primarily from product sales to hospitals, clinics, and retail channels.