
Principal Data Engineer
- Data Modeling
- AI
- Databricks
- Delta Lake
- Devops
- Fabric
- PySpark
- Apache Spark
- AWS
- Python
- SQL
- Scaled Agile
- Agile
- NoSQL
- Large Language Models
- Git
- SVN
- CI/CD
- Jenkins
- Maven
- Unit Testing
Career Category
EngineeringJob Description
Job Description
ABOUT THE ROLEÂ
 
Role Description:Â
 
Let’s do this. Let’s change the world. We are looking for highly motivated expert Principal Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management.Â
 
Roles & Responsibilities:
- Architect and maintain robust, scalable data pipelines using Databricks, Spark, and Delta Lake, enabling efficient batch 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.Â
 
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 OpsÂ
 
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 preferredÂ
 
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.
Principal Data Engineer · Amgen Inc.