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Principal Data Engineer Fulltime
Join Abbott Medical Devices as a Principal Data Engineer to lead innovative data engineering initiatives, construct optimized data architectures, and impact patient care through compelling insights. Contribute your expertise to advance medical technologies and drive data-driven decision-making. Elevate your career with Abbott’s growth opportunities and inclusive environment. Apply now!
Summarize by CVGorilla
This position works out of the Chicago, IL or Plano, TX locations in the Medical Devices Digital Solutions organization. Abbott Medical Devices, with revenue of >$16.5B in 2023, is a global leader in providing life changing technology for the management and treatment of people living with chronic conditions including Diabetes, Cardiovascular disease, Chronic Pain, and Movement Disorders. The Principal Data Engineer, Digital Solutions reports to the Head of Technology, Digital Solutions. The Principal Data Engineer role will closely work with cross-functional product teams and responsible for designing, developing, and deploying state of the art data engineering techniques and streamlined data ingestion processes to extract valuable insights and intelligence from large and complex medical datasets (structured and unstructured data). The Principal Data Engineer role will develop standards, guidelines, and direction for data modeling and data standardization that will directly contribute to enhancing the quality of patient care and the development of innovative medical devices and therapy solutions.WHAT YOU’LL DO• 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.EDUCATION AND EXPERIENCE YOU’LL BRINGRequired:• Master’s Degree in Data Science, Computer Science, Statistics, or a related field plus 10 years of experience in data engineering with a strong focus on data architecture and data ingestion.• Strong understanding of data modeling (conceptual, logical, and physical) using different data modeling methodologies and analytics concepts.• Proven experience designing, building, and maintaining data pipelines and platforms.• Expertise working with data integration and ETL tools, and data engineering programming/scripting languages (Python, Scala, SQL) for data preparation and analysis.• Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks).• 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 to convey complex technical concepts and findings to non-technical stakeholders and collaborate effectively across teams.Preferred:• Prior experience with healthcare domain data, including Electronic Health Records (EHR).• Experience with triple stores or graph databases (e.g., GraphDB, Stardog, Jena Fuseki)• Proficient with building domain ontologies and relevant W3C standards – RDF, RDFS, OWL, SKOS, SPARQL and associated Ontology Editors (e.g., TopBraid Composer, Protégé).• Experience with semantic validation languages (e.g. SHACL, SPIN) and associated semantic software packages and frameworks (e.g., Jena, Sesame, RDF4J, RDFLib).• Knowledge of data governance and compliance policies.WHAT WE OFFERAt Abbott, you can have a good job that can grow into a great career. We offer:• Training and career development, with onboarding programs for new employees and tuition assistance• Financial security through competitive compensation, incentives and retirement plans• Health care and well-being programs including medical, dental, vision, wellness and occupational health programs• Paid time off• 401(k) retirement savings with a generous company match• The stability of a company with a record of strong financial performance and history of being actively involved in local communitiesLearn more about our benefits that add real value to your life to help you live fully: http://www.abbottbenefits.com/pages/candidate.aspxFollow your career aspirations to Abbott for diverse opportunities with a company that provides the growth and strength to build your future. Abbott is an Equal Opportunity Employer, committed to employee diversity.Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal.The base pay for this position is $95,000.00 – $190,000.00. In specific locations, the pay range may vary from the range posted.
