24 days ago
Base Salary
$129k - $259k/yr
Responsibilities
- Own technical outcomes for assigned cross-domain initiatives from initial ambiguity through production and lifecycle support.
- Translate enterprise needs into integrated architectures and executable technical plans across multiple data domains.
- Coordinate technical execution across Staff Engineers and partner teams while identifying dependencies and architectural risks.
- Remain hands-on through prototyping, reference implementations, critical-path development, technical validation, design and code reviews, and production problem solving.
- Define and steward enterprise data engineering standards, patterns, data contracts, and reference architectures.
- Lead architecture for semantic and metrics layers, canonical data models, batch, API, event-driven, streaming, and governed data product capabilities.
- Mentor Staff and Senior Engineers and communicate technical tradeoffs to engineering, business, and executive stakeholders.
- Evaluate reliability, scalability, performance, security, privacy, operability, adoption, and technical cost.
- Lead enterprise technical escalations, root-cause analyses, and preventive changes for recurring issues.
- Design and review architectures handling protected health information and applicable security, privacy, lineage, audit, Quality Management System, HIPAA, CLIA, and regulatory requirements.
- Provide technical direction and due diligence for vendor and external-partner solutions.
- Work nights and/or weekends as needed.
Requirements
- Bachelor's degree in Data Science, Computer Science, Information Systems, Mathematics, or Engineering.
- Expert-level experience with software development design and development and relevant domain-specific skills.
- Experience with Spark on Databricks or comparable platforms, Python, Scala, SQL, and Snowflake.
- Experience building ETL and ELT data pipelines using batch and event-driven patterns.
- Experience designing and implementing relational, dimensional, and/or NoSQL data modeling solutions.
- Experience with database architecture testing methodology, test plans, debugging, and testing scripts and tools.
- Experience with Parquet, Avro, Delta Lake, cloud infrastructure and delivery services, AWS, S3, SQS, and GitLab CI/CD.
- Experience developing REST APIs and familiarity with BI concepts and Tableau performance considerations.
- Experience with JIRA and Confluence.
- Ability to lead through influence across multiple teams and communicate complex technical decisions to senior engineering, business, and executive stakeholders.
- Preferred experience with Databricks, Apache Spark, Delta Lake, Unity Catalog, Kafka, change data capture, production event streaming, semantic or metrics layers, canonical data models, and governed data products.
- Preferred cloud data architecture experience with AWS, Azure, or Google Cloud Platform.
- Preferred experience in life sciences, diagnostics, or clinical laboratory environments involving protected health information, HIPAA, CLIA, FDA, or Quality Management System requirements.
- 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 approximately 5% travel.
- The role may require nights and/or weekends as needed.
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.