Data Engineer (Analytics)
NavaFull Time
Junior (1 to 2 years)
Candidates should have experience in big data engineering and cloud-based analysis, with proficiency in a modern tech stack including Databricks, Redshift, S3, Lambda, DynamoDB, Spark, and Python. A strong understanding of software engineering principles and the ability to work with large, complex datasets are essential.
The Data Engineer will design and implement data pipelines for processing and visualization, develop and maintain data ingestion solutions on AWS using native services, and design and optimize data models on AWS Cloud using Databricks and AWS data stores. Responsibilities include integrating and assembling large datasets, extracting and transforming data, customizing integration tools, processing unstructured data, monitoring data performance, creating software architecture documentation, and providing technical support and code reviews to the team.
Healthcare solutions in diagnostics and devices
Abbott Laboratories focuses on improving health through various medical technologies and health solutions. The company operates in areas such as cardiovascular health, diabetes management, diagnostic testing, nutrition, and neuromodulation for chronic pain and movement disorders. Abbott's products include advanced medical devices and diagnostic tests that help healthcare professionals and patients manage health conditions effectively. For example, their cardiovascular technologies assist in heart health management, while diabetes care products enable accurate glucose monitoring without painful fingersticks. Unlike many competitors, Abbott emphasizes accessibility and affordability in its offerings, aiming to make life-changing technologies available to a broader audience. The company's goal is to positively impact global health and well-being, supported by a commitment to sustainability and a 2030 Sustainability Plan.