Data Engineer

apartmentAbbott Laboratories placeAlameda calendar_month 

Data Engineer

About Lingo

Meet Lingo, a new biosensing technology that provides users a window into their body. Lingo tracks key biomarkers – such as glucose, ketones, and lactate – to help people make better decisions about their health and nutrition. Biowearable technology will digitize, decentralize and democratize healthcare, enabling consumers to take control of their own health.

The opportunity

Personalized healthcare is the future. Working on Lingo, you will help build a next-generation technology that enables individuals to make decisions about how to improve energy, lose weight or enhance athletic performance. The Lingo team embodies a start-up culture and mindset with the backing of Abbott, a company with a rich history of healthcare innovation.

Join us and grow your career as you help Abbott shape the future of healthcare.

This position works out of our location in Lingo.

You will work closely with a multidisciplinary agile team to build high-quality data pipelines for high-end analytics solutions. These solutions will generate insights from the organization’s connected data and enable data-driven decision-making capabilities for the organization.

What you’ll do
  • Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals
  • Solve complex data problems to deliver insights that help the organization achieve its goals
  • Code in Python and Scala with tools like Apache Spark/Kafka to build a multi-cluster data warehouse
  • Interact with other technology teams to define, prioritize, and ensure smooth deployments for other operational components
  • Advise, consult, mentor, and coach other data and analytics professionals on data standards and practices
  • Foster a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytical solutions
  • Codify best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases to facilitate data capturing and management
Qualifications
  • 4+ years of relevant experience in data engineering/analytics space
  • Expertise in SQL and data analysis and strong hands-on expertise with at least one programming language: Python and/or Scala
  • Strong knowledge in one or more of the following big data tools: Hive, Hadoop Impala, Spark, Kafka
  • Strong expertise in ETL, reporting tools, data governance, data warehousing, and hands-on experience
  • Experience developing solutions for cloud computing services and infrastructure
  • Experience developing and maintaining data warehouses in big data solutions
  • Up-to-date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective
  • Experience in agile development
  • Strong people skills, specifically in collaboration and teamwork
  • High level of curiosity, creativity, and problem-solving capabilities
Apply Now
  • Participants who complete a short wellness assessment qualify for FREE coverage in our HIP PPO medical plan. Free coverage applies in the next calendar year.

Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com

Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. 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.

Divisional Information

Diabetes

We’re focused on helping people with diabetes manage their health with life-changing products that provide accurate data to drive better-informed decisions. We’re revolutionizing the way people monitor their glucose levels with our new sensing technology.

The base pay for this position is $95,500.00 – $190,900.00. In specific locations, the pay range may vary from the range posted.

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