Principal Data Engineer

ch and real-time processing.

• Lead efforts to evaluate, adopt, and integrate emerging technologies and tools that enhance productivity, scalability, and data delivery capabilities.

• Drive performance optimization efforts, including Spark tuning, resource utilization, job scheduling, and query improvements.

• Identify and implement innovative solutions that streamline data ingestion, transformation, lineage tracking, and platform observability.

• Build frameworks for metadata-driven data engineering, enabling reusability and consistency across pipelines.

• Foster a culture of technical excellence, experimentation, and continuous improvement within the data engineering team.

• Collaborate with platform, architecture, analytics, and governance teams to align platform enhancements with enterprise data strategy.

• Define and uphold SLOs, monitoring standards, and data quality KPIs for production pipelines and infrastructure.

• Partner with cross-functional teams to translate business needs into scalable, governed data products.

• Mentor engineers across the team, promoting knowledge sharing and adoption of modern engineering patterns and tools.

• Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals.

• Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architectures.

Must-Have Skills:

• Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies.

• Proficiency in workflow orchestration, performance tuning on big data processing.

• Strong understanding of AWS services

• Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures.

• Ability to quickly learn, adapt and apply new technologies

• Strong problem-solving and analytical skills

• Excellent communication and teamwork skills

• Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices.

Good-to-Have Skills:

• Good to have deep expertise in Biotech & Pharma industries

• Experience in writing APIs to make the data available to the consumers

• Experienced with SQL/NOSQL database, vector database for large language models

• Experienced with data modeling and performance tuning for both OLAP and OLTP databases

• 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

Education and Professional Certifications

• 12 to 17 years of experience in Computer Science, IT or related field

• AWS Certified Data Engineer preferred

• Databricks Certificate preferred

• Scaled Agile SAFe certification 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.

• Ability to learn quickly, be organized and detail oriented.

• 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.

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