Senior Data Engineer, Digital Solutions

Senior Data Engineer

The Data & Analytics Function oversees the analytics lifecycle to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages data products, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling.

Data Engineering ensures raw data is usable and accessible for the organization. Data Engineering encompasses numerous specialties of data acquisition, integration, and provisioning.

This role will support the Major Rugby business unit, a legacy supplier of multi-source, generic pharmaceuticals for over 60 years. Major Rugby provides over 1,000 high-quality, Rx, OTC and vitamin, mineral and supplement products to the acute, retail, government and consumer markets.

Job Overview

As a Senior Data Engineer, you will help define and implement multi-cloud-based infrastructure for Data Lake, Analytics and Machine Learning initiatives. In this critical role, primary focus is to architect, implement and operationalize large-scale enterprise data platforms, and solutions leveraging one or more of Google Cloud Platform technologies like BigQuery, PubSub, Cloud Functions, Airflow.

As a primary subject matter expert, you will be implementing and providing consultation services and leading various build and operations teams to productionize Big Data and Analytics workloads. You will build solutions that ingest, store and distribute our big data to be consumed by data scientists, data analysts and front end applications. You will leverage emerging cloud technologies to build Data Platforms and Pipelines at enterprise scale to support Analytics and ML/AI solutions. All this while leveraging agile DevSecOps (DataOps, MLOps) practices, and automation to enable speed, quality, and provide a seamless experience to internal/external customers.

Responsibilities

• Data Architecture Design: Designing and implementing Data Platforms, Data Pipeline (integration) technologies, and Common Data Services using cloud native integration and analytics technologies. Design the data infrastructure for scale and resiliency with monitoring/alerts in place.
• Technical Leadership: Provide technical guidance to data engineering teams, mentoring junior engineers on best practices for data pipeline development, data modeling, and performance optimization. Assist with integration practice integration engines to the data infrastructure.
• Data Governance: Work with data quality and information security teams to help define data quality standards, data governance policies, and data security measures to ensure data integrity and compliance.
• Hands-On Experience: Creating datasets for Machine learning algorithms and data analysis. Design and build low-code/no-code data pipeline frameworks to support large scale ingestions and practice integrations. Optimize data pipelines for cost optimized, large scale data lake implementations.
• Work closely and collaboratively with other members of the analytics teams including data scientists, business/data analysts, and product teams to define requirements, mine and analyze data, and integrate data from a variety of sources.
• Perform unit and integration data testing.
• Perform detail assessments of current state data platforms and drive enhancements and optimization activities.
• Participate in implementation of BI visualizations.
• Lead data engineering projects, including scoping, planning, execution, and monitoring, ensuring successful delivery of data solutions aligned with business requirements.
• Implement Common Data Services (e.g., Data Orchestration using AirFlow, Data Governance capabilities using Collibra) to support reuse across business functions.

Qualifications

Required proven experience in the following:

• 8+ years of engineering experience in Big Data systems, Data Analytics and Data Integration related fields preferred
• GCP experience in Cloud Infrastructure, Data Integration, Data Engineering, Cloud Analytics solutions, and experience with operationalizing enterprise scale solutions
• Architecting and designing data lakes on GCP cloud analytics, BI and Machine learning workloads
• Middleware technologies, and Data Ingestion technologies like GCP DataFlow, and AirFlow
• Writing complex SQL queries, stored procedures, etc.
• Agile development skills.
• CI/CD pipelines such as Concourse, Jenkins and Terraform technologies
• GCP Cloud cost optimization and authoring performance efficient queries
• Required experience of modern version control (GitHub)
• Experience with Databricks is preferred

Anticipated salary range: $121,600 - $173,700

Bonus eligible: Yes

Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being.

• Medical, dental and vision coverage
• Paid time off plan
• Health savings account (HSA)
• 401k savings plan
• Access to wages before pay day with myFlexPay
• Flexible spending accounts (FSAs)
• Short- and long-term disability coverage
• Work-Life resources
• Paid parental leave
• Healthy lifestyle programs

Application window anticipated to close: 9/26/2025 *if interested in opportunity, please submit application as soon as possible.

The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidate's geographical location, relevant education, experience and skills and an evaluation of internal pay equity.

Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply. Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.