Senior Data Engineer

JOB DESCRIPTION:

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 114,000 colleagues serve people in more than 160 countries.

Primary Job Function:

The Senior Data Engineer designs and implements scalable data solutions to support global Advanced Analytics (AA) within the EPD division, aligning closely with business goals and stakeholders.

Focused on enabling data-driven decision-making, this role involves building robust data infrastructures, maintaining stable pipelines, and ensuring data accessibility for AA initiatives. The engineer collaborates with cross-functional teams to scope, develop, deploy, and integrate analytics solutions, choosing appropriate tools, frameworks, and storage systems.

Key responsibilities include producing high-quality, production-ready code, modernizing legacy systems into reusable components, and co-developing shared frameworks with peers in data science and IT. The role also supports the global AA roadmap by addressing business needs and ensuring data solutions drive measurable value across the organization.

Core Job Responsibilities:

• Data Pipeline and Integration Development:

  • Build, maintain, and optimize end-to-end data pipelines that acquire, ingest, and process data from multiple sources into Big Data platforms, ensuring data availability and accessibility for AA initiatives.

  • Collaborate with business owners and subject matter experts to model data landscapes, secure data exchanges, and implement effective data integration strategies.

• Data Architecture & Cloud Environments:

  • Design and manage data environments in the Cloud with an emphasis in AWS with a strong focus on scalability, performance, and security.

  • Leverage distributed processing frameworks (e.g., Apache Spark, Hadoop, Amazon Glue) and multiple database technologies (e.g., traditional RDBMS, NoSQL, MPP) to build a robust data infrastructure for EPD’s Advanced Analytics.

• Collaboration and Best Practices:

  • Work closely with data scientists, engineers, and IT to curate, wrangle, and prepare data for advanced analytical models.

  • Help derive and continuously refine AA guidelines and standards by synthesizing learnings from prioritized initiatives (“learning while doing and driving impact”).

  • Ensure compliance with data security and privacy standards, reflecting a strong understanding of Information Security principles.

• Mentorship and Continuous Improvement:

  • Provide technical leadership and mentorship to junior data engineers, fostering a collaborative environment that bridges the gap between business requirements and technical execution.

  • Stay updated with emerging data technologies and methodologies, integrating innovative practices into the company’s AA initiatives within EPD.

Minimum Education:

• Master in relevant field (e.g., applied mathematics, computer science, electrical engineering, applied statistics)

Minimum Experience/Training Required:

• At least 4 – 6 years of relevant working experience in data engineering or related roles within larger companies or corporate environments, ideally with exposure to regulated industries such as pharmaceuticals.

• Good /solid experience working on full-life data cycle.

• Experience with real-time and sensor data is a plus.

• Proven ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets.

• Strong experience in multiple database technologies such as: Distributed Processing (Spark, Hadoop, EMR, Amazon Glue), traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (AWS Redshift, Teradata), NoSQL (MongoDB, Amazon DynamoDB, Cassandra, Neo4J, Amazon Athena)

• Programming experience in Python, Java or Scala.

• Demonstrated experience in ensuring data security and compliance for sensitive data.

• Good understanding of good software engineering principles.

• Good knowledge of testing frameworks and libraries.

• Strong experience and interest in Cloud platforms with a focus on AWS.

• Excellent problem-solving skills.

• Result-oriented analytical and creative thinker.

• Proven communication skills.

• Intrinsic motivation to guide people and make Advanced Analytics more accessible to a broader range of stakeholders.

• Ability to work with cross-functional teams and bring business and data science closer together - consultancy experience a plus.

• Fluency in English a must, additional languages a plus.

Do you like the sound of this job and think you’ve got what it takes? Then send us your CV today. We look forward to receiving your application as pdf .

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The base pay for this position is

In specific locations, the pay range may vary from the range posted.

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