4 days ago
Base Salary
$129k - $259k/yr
Responsibilities
- Own technical outcomes for assigned cross-domain enterprise data initiatives from initial ambiguity through production and lifecycle support.
- Translate enterprise needs into integrated architectures, executable technical plans, and incremental deliverables across domains.
- Define and steward enterprise data engineering standards, patterns, reference architectures, data contracts, canonical models, and governed data products.
- Remain hands-on through prototyping, reference implementations, critical-path development, technical validation, design and code reviews, and production problem solving.
- Coordinate technical execution across domain Staff Engineers and partner teams while identifying dependencies, risks, technical debt, and convergence opportunities.
- Mentor Staff and Senior Engineers and communicate architectural tradeoffs to engineering, business, and executive stakeholders.
- Evaluate reliability, scalability, performance, security, privacy, operability, adoption, and technical cost, including architectures handling protected health information.
- Serve as the enterprise technical escalation for multi-domain incidents and lead root-cause analysis and preventive improvements.
- Provide technical due diligence and architecture direction for vendor and external-partner solutions and support Quality Management System policies and procedures.
- Work nights and/or weekends as needed and maintain regular, reliable attendance.
Requirements
- Bachelor's degree in Data Science, Computer Science, Information Systems, Mathematics, or Engineering, or a high school diploma/GED with 12 years of relevant experience in lieu of the degree.
- 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, including test plans, debugging, testing scripts, and testing tools.
- Experience with Parquet, Avro, Delta Lake, cloud infrastructure and delivery services, AWS, S3, SQS, and GitLab.
- Experience with REST API development and familiarity with BI concepts and Tableau performance considerations.
- Experience using JIRA and Confluence and working with Agile development tools.
- Ability to lead through influence across multiple teams and communicate complex technical decisions to senior engineering, business, and executive stakeholders.
- Preferred experience includes enterprise-scale Databricks, Apache Spark, Delta Lake, Unity Catalog, Kafka, change data capture, production event streaming, semantic or metrics layers, canonical data models, governed data products, AWS, Azure, or Google Cloud Platform.
- Preferred domain experience includes 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
- Base pay is $129,300.00–$258,700.00, with location-specific ranges potentially varying.
- The role may require working nights and/or weekends as needed.
- Regular and reliable attendance is expected.
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.