Staff Data Engineer

$95,000 - $190,000/Yr

Abbott Laboratories - Chicago, IL

Full-time - Mid Level

Chicago, IL

10,001+ employees

Miscellaneous Manufacturing

About the position

The Principal Data Engineer at Abbott will play a crucial role in the Medical Devices Digital Solutions organization, focusing on designing, developing, and deploying advanced data engineering techniques. This position involves working with cross-functional teams to enhance patient care through innovative data solutions, managing large and complex medical datasets, and establishing standards for data modeling and ingestion processes.

Responsibilities

• Lead and contribute hands-on to major data engineering initiatives from inception to delivery.
• Analyze data to identify trends and insights.
• Collaborate with product and engineering teams to define data requirements and drive data-driven decision-making.
• Design and implement data models to effectively support various product use cases.
• Design, implement, and maintain scalable and optimized data architectures that meet evolving business needs.
• Evaluate and recommend appropriate data storage solutions, ensuring data accessibility and integrity.
• Develop and continuously optimize data ingestion processes for improved reliability and performance.
• Design, build, and maintain robust data pipelines and platforms.
• Establish monitoring and alerting systems to proactively identify and address potential data pipeline issues.
• Support Data infrastructure needs such as cluster management and permission.
• Develop and maintain internal tools to streamline data access and analysis for all teams.
• Create and deliver documentation to educate product teams on data best practices and tools.
• Communicate technical concepts effectively to both technical and non-technical audiences.

Requirements

• Bachelor's Degree in Data Science, Computer Science, Statistics with minimums of 8 years of data engineering experience, or a Master's Degree in the same fields with 6 years of relevant experience.
• Experience in the Life Science Industry.
• Strong understanding of data modeling (conceptual, logical, and physical) using different methodologies and analytics concepts.
• Proven experience designing, building, and maintaining data pipelines and platforms.
• Expertise in data integration, ETL tools, and programming/scripting languages (Python, Scala, SQL).
• Experience with Data Ops in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms.
• Familiarity with data streaming technologies like Kafka and Debezium.
• Proven expertise with data visualization tools (e.g., Tableau, Power BI).
• Strong understanding of data security principles and best practices.
• Experience with CI/CD pipelines and automation tools.
• Strong problem-solving and critical thinking skills.
• Excellent written and verbal communication skills.

Nice-to-haves

• Prior experience with healthcare domain data, including Electronic Health Records (EHR).
• Experience with triple stores or graph databases (e.g., GraphDB, Stardog).
• Proficient with building domain ontologies and relevant W3C standards.
• Experience with semantic validation languages and associated semantic software packages.
• Knowledge of data governance and compliance policies.

Benefits

• Career development opportunities with an international company.
• Free medical coverage for employees via the Health Investment Plan (HIP) PPO.
• Excellent retirement savings plan with high employer contribution.
• Tuition reimbursement and student debt programs.
• Recognition as a great place to work in various countries and for diversity.