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Amgen Inc
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Principal Data Engineer

Principal Data Engineer

Amgen Inc

12 - 17 years

10 - 14 Lacs

hyderabad

Posted:1 day ago| Platform:

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Skills Required

performance tuning data processing presentation skills troubleshooting big data continuous integration python aws iam workflow orchestration pyspark ci/cd sql nosql data bricks git data modeling spark devops jenkins agile aws

Work Mode

Work from Office

Job Type

Full Time

Job Description

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.

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.

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.

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Principal Data Engineer