Data Engineering Senior Manager

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.

ABOUT THE ROLE

Role Description:

We are seeking a seasoned Senior Engineering Manager (Data Engineering) to drive the development & maintenance of data pipelines developed by data engineering teams focusing on deep domain expertise of HR/Finance data. This role will lead a team of data engineers who will be maintaining data pipelines, and operational frameworks that support enterprise-wide data solutions. The ideal candidate will drive best practices in data engineering, cloud technologies, and Agile development, ensuring robust governance, data quality, and efficiency. The role requires technical expertise, operational excellence and a deep understanding of data solutions to optimize data-driven decision-making.

Roles & Responsibilities:

• Lead and mentor a high performing team of data engineers who will be developing and maintaining the complex data pipelines.
• Drive the development of data tools and frameworks for managing and accessing data efficiently across the organization.
• Oversee the implementation of performance monitoring protocols across data pipelines, ensuring real-time visibility, alerts, and automated recovery mechanisms.
• Coach engineers in building dashboards and aggregations to monitor pipeline health and detect inefficiencies, ensuring optimal performance and cost-effectiveness.
• Lead the implementation of self-healing solutions, reducing failure points and improving pipeline stability and efficiency across multiple product features.
• Oversee data governance strategies, ensuring compliance with security policies, regulations, and data accessibility best practices.
• Guide engineers in data modeling, metadata management, and access control, ensuring structured data handling across various business use cases.
• Collaborate with business leaders, product owners, and cross-functional teams to ensure alignment of data architecture with product requirements and business objectives.
• Prepare team members for stakeholder discussions by helping assess data costs, access requirements, dependencies, and availability for business scenarios.
• Drive Agile and Scaled Agile (SAFe) methodologies, managing sprint backlogs, prioritization, and iterative improvements to enhance team velocity and project delivery.
• Stay up-to-date with emerging data technologies, industry trends, and best practices, ensuring the organization leverages the latest innovations in data engineering and architecture.

Functional Skills:

Must-Have Skills:

• Experience managing a team of data engineers in biotech/pharma domain companies.
• Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.
• Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
• Proficiency in Python, PySpark, SQL.
• Experience with dimensional data modeling.
• Experience working with Apache Spark, Apache Airflow.
• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops.
• Experienced with AWS or GCP or Azure cloud services.
• Understanding of end-to-end project/product life cycle.
• Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
• Strong analytical and problem-solving skills to address complex data challenges.
• Effective communication and interpersonal skills to collaborate with cross-functional teams.

Good-to-Have Skills:

• Data Engineering Management experience in Biotech/Life Sciences/Pharma
• Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.

Education and Professional Certifications

• 12 -15 years of experience in Computer Science, IT or related field  
• AWS Certified Data Engineer preferred
• Databricks Certificate preferred
• Scaled Agile SAFe certification preferred
• Project Management certifications preferred

Soft Skills:

• Excellent analytical and troubleshooting skills
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation
• Ability to manage multiple priorities successfully
• Team-oriented, with a focus on achieving team goals
• Strong presentation and public speaking skills

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.